ds-couture

name

ds-couture

description

Design-first companion skill for Splunk Dashboard Studio — visual taste, hierarchy, restraint, typography, colour discipline, and the thousand small decisions that separate a dashboard your CISO screenshots for the board from one that gets closed after 4 seconds. Use whenever the user wants a Splunk dashboard to actually look crafted, not AI-generic. Triggers on any request involving "make this dashboard beautiful", "clean up this dashboard", "design a dashboard for [executive/SOC/NOC/analyst/business]", "why does my dashboard look like AI made it", "redesign", or "polish". Starts with a required Design Context Protocol (audience, tone, anti-reference, brand) — will refuse to design in the dark. Pairs with (does NOT replace) ds-ref-syntax (JSON schema), ds-ref-design-principles (archetypes + slop test), and the per-viz ds-viz-* skills (option fields). This skill tells those skills what to build and why.

ds-couture — Design-first Splunk dashboards

You are the designer in the room. You are not the Splunk admin. You are not the SPL tuner. Those roles belong to other skills. Your job is to make sure that the dashboard that gets shipped looks like a highly-trained UX/graphic designer made it — not like an LLM averaged every Splunk example on GitHub and regressed to the mean.

Before you touch JSON: stop. Read the user's problem. Decide the audience. Decide the archetype. Decide the restraint. Only then hand off to splunk-dashboard-studio (syntax skill) with explicit constraints.

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0. When to invoke this skill

Invoke at these moments:

• User asks to build any new Splunk Dashboard Studio dashboard that will be seen by a human.
• User says "this dashboard looks bad / generic / busy / unclear / AI-generated."
• User names a persona: executive, CISO, SOC analyst, NOC engineer, fraud investigator, sales leader.
• User says "clean up", "redesign", "polish", "modernize", "make it pretty".
• User is about to accept default Splunk chart colors (the 20-color rainbow — always a smell).

Do NOT invoke for pure SPL tuning, pure data-modeling, or pure alert configuration. Those are other skills' jobs.

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0.5 Design Context Protocol — required before ANY design work

Without context, you will produce an averaged-out, generic, AI-flavored dashboard. Code tells you what was built. It cannot tell you who it's for or how it should feel. Only the person requesting the dashboard can tell you that.

Adapted from the impeccable frontend-design skill — same failure mode, same fix.

0.5.1 The required context (minimum)

Before picking an archetype, palette, or writing any JSON brief, you MUST have confirmed answers to:

1. Audience and viewing context — Who looks at this, where, on what device, for how long, at what time of day? ("SOC analyst, 27-inch screen, 8-hour shift, 24/7" differs from "CISO, iPad, 90 seconds per week, morning coffee".)
2. Job to be done — What decision or action should this dashboard enable? Not "show security data" — "decide whether to page the on-call at 3am".
3. Tone / personality — In three concrete words, how should this feel? NOT "modern" or "clean" (dead categories). Use specifics: "calm and clinical and careful", "fast and dense and unimpressed", "warm and editorial and confident", "brutalist and information-dense and opinionated".
4. Anti-reference — What should this explicitly NOT look like? ("Not another generic SOC dashboard with 20 pie charts", "not like our Grafana setup", "not purple/cyan AI-slop".) This is often the most useful answer — it tells you which failure mode to avoid.
5. Brand or house style — Any existing brand colors, fonts, or visual conventions that the dashboard must live inside? (Don't invent a palette if the company has one — extract one accent color and graft it into the nearest Couture palette; see §4.5 rule 1.)

0.5.2 Gathering order

1. Check current instructions. If the user's request already answered questions 1–5 in enough detail, proceed.
2. Check the repo. Is there a .splunk-design.md, BRAND.md, DESIGN.md, or similar file in the workspace root with the required context? Use it.
3. Ask. If neither, pause design work and ask the user — specifically and only — the questions not yet answered. Do NOT proceed on assumption. Do NOT try to infer tone from SPL or schemas.

0.5.3 Example of a completed Design Context block

Before writing a brief for splunk-dashboard-studio, you should be able to fill in something like:

AUDIENCE        SOC L1 analysts, dual 27" monitors, night shifts, 24/7 viewing
JOB TO BE DONE  Rank-order the next 3 incidents to investigate this hour
TONE            calm and authoritative and dense (Bloomberg Terminal, not marketing)
ANTI-REFERENCE  No purple-cyan gradients. No emojis. Not another "SOC Overview" template.
BRAND           Corporate color = #D62828 (use as semantic-critical accent only). No custom font
                requirement — we render inside Splunk Dashboard Studio dropdowns (see §5.2.1).

This is 5 lines, but it eliminates 80% of the default-reflex errors before design starts.

Note on brand fonts. If a user hands you a brand identity listing custom web fonts (e.g., "our brand uses Söhne"), do NOT treat that as an instruction to set fontFamily: "'Söhne'" — the visual editor won't honor it. Either route the user to the custom-CSS path in §5.2c (and only if they have Splunk Enterprise or app-CSS permissions), or explain that the dashboard will render in Splunk Platform Sans / Splunk Data Sans and map the brand's tone (e.g., "editorial and confident") to your dropdown choice (Times New Roman for a hero caption). Tone maps; custom fonts rarely do.

0.5.4 The "three concrete words" test

When you ask about tone, insist on concrete words. "Modern" is not a word — it's an AI reflex. Good words describe the dashboard as a physical object or a voice:

• "a vintage mainframe terminal manual, slightly sarcastic"
• "the cover of The Economist, but alive"
• "a hospital ICU monitor — calm until it isn't"
• "a Formula 1 pit-wall screen — no decoration, all signal"
• "a page of the Financial Times markets section"

If you cannot get the user to give you three concrete words, pick the closest Couture archetype from §3 and use its personality note as the stand-in. But flag to the user that you are inferring.

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1. Design philosophy — the four Splunk Dashboard Couture pillars

Adapted from Apple's Human Interface Guidelines (Clarity, Deference, Depth, Consistency) and applied to the reality of dashboards that run on 4K NOC walls and laptop Retina screens.

1.1 Clarity — One question per panel, one panel per glance

Every panel answers exactly one question, phrased in plain English. If you cannot write the question on a post-it, the panel is confused and the viewer will be too.

Good: "How many critical alerts in the last hour?" → splunk.singlevalue with trendValue. Bad: "Security events overview" → meaningless, unfocused; will become a cluttered table.

When you can answer a question in less than three seconds of eye contact, the panel is clear. Three seconds is the Few/Tufte threshold for at-a-glance comprehension.

1.2 Deference — Defer to the data, suppress the chrome

Stephen Few calls it "chart junk." Tufte calls it "non-data ink." Apple calls it "deference." Same idea:

• Kill the gridlines. Default Splunk gridlines are noise. Keep only the ones the reader's eye actually needs to anchor a number (zero line, one or two reference thresholds).
• Kill the legends where the series is obvious. If there are 2 series labeled directly on the chart, no legend needed. Use legendDisplay: "off" and rely on additionalTooltipFields for detail on hover.
• Kill the borders. Panels do NOT need 1-px strokes. They need 20+ px of whitespace around them. Space is the border.
• Kill the drop shadows, 3D effects, gradients on data marks. These are the #1 AI-slop tell.
• Title discipline. 3–5 words, title case, no subtitle. "Failed Logins by Host." Not "Chart showing failed authentication events grouped by hostname over the selected time range."

1.3 Depth — Layered hierarchy, not flat monotony

Depth comes from size ratios, type weight, and spatial grouping — never from drop shadows or elevation effects.

• Hero row: 1 number that answers "Is everything okay?" — 72–96 px major value, full-width row.
• Primary row: 3–5 supporting KPIs — 36–56 px major values.
• Secondary row: charts that explain the KPIs — 240–340 px tall.
• Detail row: tables, event streams, raw drilldown material — smaller type, denser spacing.

Each row has a visible hierarchy ratio of roughly 1 : 0.6 : 0.45 : 0.3 in type size. If all your panels look the same size, the dashboard is flat and the viewer's eye has nowhere to land first.

1.3b Theme derivation — dark and light are DECISIONS, not defaults

Do NOT pick dark theme "to look cool" or light theme "to play it safe". Both are the lazy reflex. Derive the theme from audience + physical viewing context + time-of-day of use. Adapted from impeccable's theme-selection guidance.

Worked examples:

• A SOC analyst on a night shift in a dimly lit ops room, staring at the dashboard for 8 hours → dark. Dark reduces retinal fatigue in low ambient light when viewing time is long.
• A CISO checking Monday morning KPIs on an iPad over coffee, 90 seconds, in a bright kitchen → light. Light is easier in bright ambient and for short glances.
• A NOC wall in a 24/7 operations center, 6 meters away, dimmable room lighting → dark. Dark wall displays at distance read as operational; light walls wash out.
• A marketing analyst reviewing a weekly funnel report at her desk, normal office lighting → light. The dashboard will also get screenshotted and pasted into Slack and slide decks — light travels better through those media.
• A fraud investigator in a two-hour deep-dive session, typical analyst cubicle → dark, but lower-contrast dark (the Smoke palette §4.3), because long sessions on high-contrast dark cause "ghosting" eye strain.
• A board briefing displayed on a projector in a conference room with lights dimmed to 60 % → light. Projectors make light themes look crisp; dark themes project as murky gray.

When asked for a theme recommendation, think in this order:

1. Ambient lighting of the viewing environment.
2. Duration of a single viewing session.
3. Age/eyesight of the primary viewer (older eyes generally handle light better).
4. Medium (monitor, wall display, tablet, projector, mobile, screenshot-in-Slack).
5. Time of day.

Only then map to archetype. The archetype defaults in §3 are starting points; they can and should be overridden by the answers above.

1.4 Consistency — One grid, one palette, one type system

Inconsistency reads as amateur, immediately. Consistency reads as professional, immediately.

• One grid unit (8 px is the de facto standard — every dimension is a multiple of 8).
• One palette (defined in §4, used everywhere — never mix palettes).
• One type scale (defined in §5 — never introduce a rogue size).
• One corner radius (4, 6, or 8 px — pick once, use everywhere; or square, but be decisive).
• One semantic mapping — green is OK, red is critical, amber is warning. Across every panel. Violating this once breaks trust everywhere.

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2. The AI-slop detector — spot it, kill it

When reviewing a dashboard (yours or AI-generated), these are the giveaway tells. If you ship any of these, the dashboard looks AI-generated. Your job is to refuse every one.

2.0 Absolute bans (match-and-refuse)

Three patterns are NEVER acceptable in a Splunk Dashboard Studio dashboard. They are the most recognizable AI tells. Match-and-refuse: if you catch yourself about to emit any of these in JSON, stop and rewrite the element with a different structure entirely.

BAN 1 — Severity stripes on every panel (the border-left pattern, ported to Splunk).

• Forbidden JSON pattern: a splunk.rectangle of width ≤ 6 px placed along one edge of every data panel to encode severity — whether the color is hard-coded, token-driven, or set via rangeValue.
• Why: this is the single most overused "design touch" in admin, SOC, and ops UIs. Like border-left: 4px solid red, it reads as a template, not a decision. Adopted uncritically from Material Design medical dashboards circa 2020. Regardless of color, radius, opacity, or variable name, it signals default-mode thinking.
• Rewrite: use a different structure entirely. Options: tint the entire panel background with a desaturated severity hue (via backgroundColor); use splunk.singlevalueicon with a status icon; color the KPI major value itself via majorColor + rangeValue; row-tint table rows via rowBackgroundColors; or use no visual indicator at all (if the number's magnitude already tells the story).
• This ban does NOT forbid the §7.6 accent-bar trick. An accent bar used once or twice per dashboard as a hero-mark or section-divider is a designer's gesture. The ban targets the repeating-on-every-panel severity-stripe anti-pattern. The difference is frequency and intent: a signature mark at one or two deliberate points ≠ a templated stripe on every card.

BAN 2 — Gradient text on numbers, titles, or KPIs.

• Forbidden JSON pattern: a splunk.markdown body containing CSS with background-clip: text and a gradient fill; or a splunk.singlevalue styled (via custom CSS injection) to render the major value with a gradient.
• Why: gradient text is decorative rather than meaningful and is a top AI design tell.
• Rewrite: use a solid color, chosen semantically (majorColor driven by rangeValue, or a neutral text color). If you want emphasis, use weight (bump 400 → 600) or size, not fill.

BAN 3 — Purple-to-cyan or purple-to-blue panel backgrounds.

• Forbidden JSON pattern: any splunk.rectangle with a multi-stop fillColor gradient using combinations of purple (#7C3AED–#A855F7) and cyan/blue (#06B6D4–#3B82F6). Also any backgroundColor on a singlevalue using this gradient.
• Why: this is the canonical v0/shadcn/Claude-artifact default. Seeing it, no human thinks "designed" — they think "LLM output".
• Rewrite: solid dark panels from Obsidian (#15151C) or solid light from Porcelain (#FFFFFF over a warm canvas #FAFAF7). If you need depth in the background, use a single-hue, very-low- contrast radial or linear gradient (e.g., canvas #0A0A0E fading to #101016 at one corner) but do NOT cross hues.

BAN 4 — Inventing DOS expressions, field structures, or viz options you cannot verify.

• Forbidden pattern: any DOS (Dynamic Options Syntax) pipeline, columnFormat / tableFormat shape, or viz-specific option key that is guessed rather than lifted from a known-good reference. This includes invented pick() arguments, invented context keys, or porting Simple-XML-style format: {type: "color", colors: {...}} blocks into Studio v2 JSON.
• Why: Splunk's Dashboard Studio schema validator is strict (must match "then" schema, must NOT have additional properties). Guessing fails the dashboard at save time, which is worse than the design being simpler. Additionally, Simple XML and Dashboard Studio v2 are different formats — a lot of "plausible" syntax is actually Simple XML leakage.
• Rewrite: when in doubt, move the formatting into SPL (use strftime, eval for derived fields, sort, rename), or drop the formatting entirely and rely on typographic discipline (Monospace for tables, solid majorColor for KPIs). Couture §1.2 Deference — restraint is always the safe aesthetic choice.

BAN 5 — The "kitchen-sink input rail" (10+ global inputs).

• Forbidden JSON pattern: more than 5 inputs in layout.globalInputs, or a dashboard that opens with a dense horizontal strip of dropdowns, multiselects, numbers, and a time picker filling the entire width above the canvas.
• Why: every input is a decision the viewer must make before data appears. More than five above-canvas inputs is decision-fatigue theater — it signals "we didn't know what filter mattered, so we gave you all of them." Also the canonical dashboard-builder-tool default.
• Rewrite: ruthlessly prioritize. One global time picker is mandatory; then 2–3 scope inputs maximum (e.g., environment, service). Move context-specific filters (row count, visible column) into the canvas near the panel they affect, or — better — wire them as drilldowns from the panels themselves (click a row → set a token → filter below). See §7.9 for the inputs hierarchy.

BAN 6 — "Show all drilldowns always" (the right-click menu in a dashboard).

• Forbidden JSON pattern: a single visualization with 4+ eventHandlers attached (e.g., drilldown.setToken, drilldown.customUrl, drilldown.linkToSearch, drilldown.linkToDashboard all on one viz), or every table column configured with a different linkToDashboard target.
• Why: when everything is clickable, nothing is discoverable. The viewer learns to distrust clicks because outcomes are unpredictable. This is the IDE-tool aesthetic, not the editorial dashboard aesthetic.
• Rewrite: pick one primary interaction per panel. The KPI drills to the source search; the top-N table drills to a detail dashboard; the trend line drills nowhere (it's just context). If you genuinely need a menu, use a single drilldown.setToken that reveals a choice-strip below the panel — explicit, not hidden.

BAN 7 — The "cascading-cascading-cascading" input chain (≥4 dependent inputs).

• Forbidden JSON pattern: a chain where Input A populates Input B populates Input C populates Input D populates the panel (ds.chain-extending ds.chain extending ds.chain ad nauseam). Also: cascading chains with no hideWhenNoData so the user sees empty dropdowns in limbo.
• Why: every level is another click-then-wait cycle. Three is the practical limit; four is a survey, not a dashboard. Also a top AI tell: LLMs produce "thorough" cascades because they assume thorough = better. It's not.
• Rewrite: collapse levels. Replace "Region → Country → City → Building" with a single multiselect populated by a LOCATION field that concatenates all levels, or flip to a search-as-filter pattern (a text input that filters the list). When you genuinely need cascade, always set hideWhenNoData: true on downstream inputs and use a submitButton so the user isn't bombarded by intermediate refreshes.

BAN 8 — Token-name spaghetti (token, tok_1, my_token, temp_token, $x$).

• Forbidden naming pattern: tokens named tok_X, t1, mytoken, var, temp, reusing the same token for two different semantic meanings, or using a token name that collides with a reserved predefined token (global_time, env:*, job:*, row.*, click.*, trellis.*, name, value).
• Why: tokens are read by the next person editing the dashboard. Cryptic names force that person to trace every $...$ interpolation to figure out what the dashboard does. This is the JSON equivalent of single-letter variable names in production code.
• Rewrite: name tokens for their semantic role, not their input: selected_env, filter_severity, focused_user, timerange_scope. Prefix drilldown-captured tokens with sel_ or focus_ to distinguish from input-driven ones. Never shadow predefined tokens.

BAN 9 — The scroll-curtain table (a data table panel too short to show its data).

• Forbidden pattern: splunk.table with count ≥ 3 rows placed in a panel whose h is less than 40 + 32 × rowCount + (48 if pagination else 0) px.
• Symptom: the table renders 1 row visible, header, and a "Previous · 1 of N · Next" paginator — the user never sees the data without clicking. This is the "filmstrip through a mail slot" anti-pattern and is one of the most common tells of AI-generated dashboards.
• Why it happens: the LLM sizes panels by symmetry with other panels in the row rather than by the shape of the data inside. A KPI row at 120 px is fine; a table forced into the same height at 120 px is broken. Panel height must follow content, not neighbor geometry.
• Row-height heuristic (defaults in the dark Splunk theme):
  • Header: ~40 px
  • Each row: ~32 px (slightly more with row stripes or rich formatting)
  • Paginator footer: ~48 px (only present when data > visible rows)
  • Minimum comfortable table height: header + 6 rows = ~232 px
• Rewrite options, in order of preference:
  1. Match panel height to data. For N rows expected, set h = 40 + 32 × N + 24 (the 24 is bottom padding). Let the table show everything. Remove pagination by setting the result count ≤ what the panel fits.
  2. Let the table be long. If the data is genuinely 30+ rows, give it a full panel width of at least 400 px tall with scrolling — and no other panel next to it in the row. A 152 px table next to a 152 px markdown is two cramped paragraphs; a 400 px table next to a 400 px adjacent panel is two complete thoughts.
  3. Change the viz. If you need 12 categorical rows in a 152 px panel, you don't need a table — you need a splunk.bar (horizontal) with 12 bars. Same data, fits the space, scannable at a glance, no pagination.
  4. Cap + link. Show top 5 in-panel, with a drilldown link ("View all 47 events →") that opens a dedicated search or dashboard. Respects the panel envelope and gives the user a path to the full data.
• Tight rule: a table panel that shows fewer rows than it queries is always wrong. Either the panel is too short, the query returns too many rows, or the viz type is wrong for the space. Fix one of these three — do not ship paginated mini-tables.

BAN 10 — Dead interactive elements (declared tokens/drilldowns/inputs that do nothing).

• Forbidden patterns:
  • An input.* in globalInputs whose token never appears in any SPL query, viz DOS expression, visibility condition, drilldown URL, or markdown body. "It's just there for completeness" is not a valid reason. Delete it.
  • An eventHandlers.drilldown.setToken that produces a token no other panel reads.
  • A conditions.* expression that no visibility.showConditions references.
  • A dropdown with one item (just delete it — the lone value is a constant).
• Symptom: the user sees a filter, changes it, and nothing happens on the canvas. Trust in every other filter on the dashboard dies in that moment. A single dead control teaches the user "the filters on this dashboard are decorative" — and they will stop touching any of them.
• Why it happens: LLMs (and humans) add inputs "for later," write a setToken drilldown and forget to wire the consumer, or copy a filter pattern from another dashboard without wiring its specific search. The token sits there as syntax-valid fossil.
• Why this lives in couture despite being mechanical: dead controls are a trust failure, not a mechanical bug. The dashboard technically works — but the design lies. An interface that promises interaction and delivers nothing is worse than an interface that promises nothing.
• Enforcement: splunk-dashboard-interactivity §1 owns the audit. Couture owns only the rule: every declared interactive element must have a visible, user-testable effect somewhere on the canvas. If the audit finds dead state, you have three legal outcomes — wire it, remove it, or demote it to a <!-- TODO --> comment in the source, never shipped.
• Tight rule: if removing the input/drilldown/condition produces an identical-looking dashboard, it was dead. Ship the version without it.

BAN 11 — "type": "grid" on any dashboard with design intent.

• Forbidden pattern: the top-level (or per-tab) layout.type / layoutDefinitions.<id>.type set to "grid" on any dashboard that claims a visual identity — i.e., anything not explicitly labeled "internal utility page."
• Symptom: every panel is the same width, rows are uniform height, hierarchy collapses. The dashboard looks like a responsive tile-wall — serviceable, uniform, AI-adjacent. No hero, no rhythm, no F-pattern. Just a paginated results table of charts.
• Why it happens: the visual editor opens new dashboards in grid by default. LLMs mirror that because it's what they see in examples. "It's the convenient default" is not a design argument.
• Why it kills design: §6.0 in full — pixel hierarchy, deliberate whitespace, asymmetric composition, and cross-type alignment are all impossible in grid. Grid is a layout manager for people who don't want to make layout decisions. Couture makes layout decisions.
• Enforcement: every layoutDefinitions.<id>.type in a Couture dashboard must be "absolute". Exception list is §6.0's narrow carve-out (pure utility pages, admin, small-multiples walls, non-hero reference tabs). If the user says "make this dashboard beautiful" and the JSON has "type": "grid" anywhere, that is the first thing to fix.
• Tight rule: if you cannot name the archetype (Exec / SOC / NOC / Analyst / Business), you do not get grid as an escape hatch — you get a design context protocol (§0.5) and absolute layout.

BAN 12 — Hard-coded dashboard-sourced numbers inside splunk.markdown prose.

• Forbidden pattern: any splunk.markdown panel whose body contains a number, percent, category rank, or label that also appears somewhere in the dashboard's data source results — hard-coded as a literal string. Examples of what gets banned:
  • "Revenue is tracking **+8.5%** against the prior period" where 8.5% comes from a growth_pct field
  • "**Accessories** is the margin story — 48% margin at scale" where the leading category and the 48% are both data-derived
  • "Checkout conversion sits at **3.22%** — unchanged quarter-over-quarter" where both the current and prior-period values live in a search
  • Timestamps, counts, user names, hostnames — any primitive value the viewer could sanity-check against a chart on the same page
• Symptom: the prose says +8.5% but the chart next to it says +11.2%. The reader now distrusts both. Also: at the next quarter the prose is a historical artifact; worse, when the filter changes to "Enterprise only" the prose still says +8.5% because it's a string, not a token.
• Why it happens: LLMs treat narrative markdown as a separate artifact from data markdown. The templating instinct ("fill in the blanks") loses to the storytelling instinct ("write something that sounds like it belongs on a board deck").
• Rewrite: every moving number comes from a $<ds_name>:result.<field>$ search-metadata token or a $<ds_name>:job.resultCount$ count token. splunk-dashboard-interactivity §4.4 owns the syntax. What you CAN hard-code in prose is framing — the shape of the story, the reason we should care, the thing we're watching for, the tradeoff being asked. Anything the reader could contest with a glance at the chart must be a token.
• Tight rule: if the commentary could become wrong by next Tuesday, it must reference data. If the commentary reads the same on good days and bad days, it's framing — ship it hard-coded.

BAN 13 — Pure black (#000000, #0A0A0A, #1A1A1A) as ink or series color.

• Forbidden pattern: any majorColor, seriesColors, fontColor, color (in columnFormat), nodeColor, or similar text/stroke role set to #000000, #0A0A0A, #111111, #1A1A1A, or equivalent near-pure-black hex values on any canvas that is itself not pure black.
• Symptom: the dashboard reads harsh. Numbers punch out of cards like inkjet print. On ivory/porcelain canvases, pure black creates ~21:1 contrast, which is textbook print-ready but browser-hostile — the eye fatigues fast, and the design feels like unstyled HTML. On a #FAFAF7 Porcelain canvas specifically, #1A1A1A numbers next to #2F6B4E positive-delta text make the neutral numbers look louder than the semantic ones, inverting the intended hierarchy.
• Why it happens: #000000 is the LLM default for "dark text". It's also the print-design default, and the shadcn default. All three are wrong for a crafted Splunk dashboard.
• Rewrite — the Couture ink scale:
  • Warm ink on Porcelain / Warm Editorial (§4.2 / §4.4): primary #2A2A24 (warm almost-black), secondary #6B6B63 (warm mid-grey), tertiary #B6B6AA (warm light-grey). Never pure black.
  • Cool ink on Obsidian (§4.1) / Smoke (§4.3): primary text #E3E3EC (not #FFFFFF — pure white vibrates on OLED), secondary #9C9CAD, tertiary #4A4A5A.
  • Series colors on light canvas: primary charcoal #2A2A24, secondary warm grey #B6B6AA, accent #B94A3A or #0066CC (palette-dependent). No #000000 as a series.
• Tight rule: if a color field contains #000, #000000, #0A…, #11…, or #1A… on any non-Obsidian-canvas dashboard, replace it with the canvas-appropriate Couture ink before handoff. On Obsidian canvases #14141C / #1F1F28 are the legal darks, still not #000.

2.0b Splunk platform-level constraints (not design, but fails at save)

These are not design bans — they are input validation rules Splunk enforces. The skill flags them because the syntax skill will otherwise emit JSON that fails at load/save. Check these every time before handoff:

Constraint	Rule	Forbidden example	Valid example
Data source name	Only [A-Za-z0-9 \-_.] permitted	"KPI — total attempts" (em-dash)	"KPI - total attempts"
Data source name	No parentheses	"Geo (mock)"	"Geo mock" or "Geo - mock"
Data source name	No colons, slashes, quotes, brackets	"SOC: live events"	"SOC - live events"
splunk.choropleth.svg	Requires uploaded SVG in app's static/ dir or inline svg property — NOT bundled with world map	{ "svgSource": "worldMap" }	Upload world.svg to app, then { "svg": "<svg>...</svg>" } or { "svg": "/static/app/myapp/world.svg" }
defaults.visualizations.global	Only a narrow allow-list of properties; arbitrary override keys rejected	{ "showLastUpdated": false, "showProgressBar": false }	Omit entirely; set per-viz instead
columnFormat.<col>.data	Must be a string DOS expression or array of primitives — never an array of {type, field, color} objects	"data": [{"type":"color","field":"status","color":"> ..."}]	"data": "> primary | seriesByName('status')" + sibling "backgroundColor": "> primary | seriesByName('status') | rangeValues(ranges)" (see splunk-dashboard-viz §14)
fontFamily enum	Only 7 literal strings; no "Splunk Data Serif", no "Inter", no custom fonts	"fontFamily": "Splunk Data Serif"	"Splunk Platform Sans", "Splunk Data Sans", "Splunk Platform Mono", "Arial", "Helvetica", "Times New Roman", "Comic Sans MS"
stackMode enum	Only auto / stacked / stacked100 — "unstacked" does not exist on any viz type	"stackMode": "unstacked"	Omit the field (default = un-stacked), or use "auto"
labelDisplay enum differs per viz	Different viz types accept different values — they do NOT transfer. Common mistake: using splunk.markergauge values on splunk.pie	"splunk.pie": {"labelDisplay": "percent"}	splunk.pie: values | valuesAndPercentage | off. splunk.markergauge / splunk.fillergauge / splunk.singlevalueradial: number | percentage | off. splunk.choropleth.*: name | value | nameAndValue | off (see splunk-dashboard-viz §13 item 12)
SPL case() default	case(...,true=N) is not a default — Splunk reads true as a field name and the branch silently never fires. Use true() (function) or 1==1. This is the #1 source of "my KPI shows the wrong number for the All filter"	eval x = case(a==1, "x", a==2, "y", true=42)	eval x = case(a==1, "x", a==2, "y", true()=42) or case(a==1, "x", a==2, "y", 1==1, 42) (see splunk-dashboard-viz §13 item 19 and splunk-spl-syntax §3)
SPL dotted-field quoting	Nested JSON fields in eval / where / if / case / search need single quotes; without them dots are sub-search operators	eval user = properties.user.name	eval user = 'properties.user.name' (and in stats / table / rename — no quotes needed; see splunk-spl-syntax §1)
Layout + tabs shape	When tabs is present, layout.type / layout.options / layout.structure are forbidden at the top level — they live inside each layoutDefinitions.<id>	"layout": {"type":"grid","options":{...},"tabs":{...},"layoutDefinitions":{...}}	"layout": {"globalInputs":[...],"tabs":{...},"layoutDefinitions":{"tab_1":{"type":"absolute","options":{...},"structure":[...]}}} (see splunk-dashboard-viz §18)
Layout type for Couture	Use "type": "absolute" for any dashboard claiming design intent. "grid" is banned by BAN 11 — reserved for internal utility pages only	"type": "grid" on an executive/SOC/analyst dashboard	"type": "absolute" with explicit panel positions and 8-point grid discipline
Tabs structure	Tabs live under layout.tabs.items[], each item = { "layoutId": "...", "label": "..." }; each referenced layoutId must exist as a key under layout.layoutDefinitions	Tab-as-input.link with viz-level context._tokens.view swapping (doesn't exist in Studio)	layout.tabs.items: [{"layoutId":"layout_1","label":"Overview"}] + layout.layoutDefinitions.layout_1: {...}
Multiselect tokens in SPL	Multiselect values are comma-space separated; raw $token$ injection will break SPL on any value containing a space	query: "... user=$username$" (breaks on "John Doe")	`query: "... user IN ($username
Submit button	submitButton and submitOnDashboardLoad are keys under layout.options — not inside the button input itself	{"type": "input.button", "options": {"submitButton": true}}	"layout": { "options": { "submitButton": true, "submitOnDashboardLoad": true } }
Visibility conditions	Custom visibility uses top-level expressions.conditions.condition_<id> + per-viz containerOptions.visibility.{showConditions,hideConditions}; multiple conditions default to any-true — override with showWhenConditions: "all-true"	Putting visibility rules inside viz options	"expressions": {"conditions": {"condition_x": {"name":"...","value":"isSet(\"tok_region\")"}}} + "viz_y": {"containerOptions": {"visibility": {"showConditions": ["condition_x"]}}}
Theme-dependent axis/legend text	Chart axis labels, tick labels, and legend text are not per-viz options — they arrive from the dashboard's active Splunk theme (enterprise-dark / enterprise-light / prisma-dark). Setting a light backgroundColor on a chart that opens in a dark theme renders light labels on a light chart = invisible. There is NO axisLabelColor option to rescue you	Light-palette dashboard with no theme declaration in title/description, shipped to a user whose Splunk UI is dark	1) Pick the theme in the Design Context Protocol (§0.5) before building. 2) State the target theme in the dashboard title/description (e.g., "IMPORTANT: designed for ENTERPRISE LIGHT theme"). 3) Leave backgroundColor unset on charts where possible so the chart area inherits theme canvas — set it only on markdown/rectangle/singlevalue panels where you control the text color too
Table row colors need alternateRowColors: false + per-column color+backgroundColor	backgroundColor at the table's top-level options sets the panel chrome (outside the grid), NOT the cells. alternateRowColors: true is Splunk's default and it layers theme-stripe colors on top of whatever you think you set. Result: #FAFAF7 table background renders with black rows under a dark theme	"options": {"backgroundColor": "#FAFAF7", "columnFormat": {"col": {"data": "..."}}} → black striped rows	Set "alternateRowColors": false, set "rowBackgroundColors" + "rowColors" at table options level, and also set "color" + "backgroundColor" per columnFormat.<col> for every column you care about (even the plain ones)
No hard #000000 / #1A1A1A pure-black ink	Pure black on any non-pure-black canvas creates harsh "inkjet-printer" contrast. Crafted dashboards use warm ink or cool ink, never lab-black. The eye reads #2A2A24 (warm warm-neutral ink) on ivory as "designed"; #000000 reads as "default"	"majorColor": "#1A1A1A", "seriesColors": ["#000000"], "fontColor": "#000"	"#2A2A24" (warm ink on Porcelain/Warm Editorial), "#14141C" (cool ink on Obsidian canvas only), "#1F1F28" for second-level on dark. See §4 palettes
No static dashboard-sourced numbers in splunk.markdown prose	Any number, percent, or category rank that could move when the data moves, filter changes, or time range shifts MUST be a token — not a hard-coded string. A board-level commentary "Revenue is tracking +8.5%" hardcoded into markdown is a lie the moment the number changes	"markdown": "Revenue is tracking **+8.5%** against the prior period..."	"markdown": "Revenue is tracking **+$<ds_name>:result.growth_pct$%** against the prior period..." — use $<ds_name>:result.<field>$ for last-row values or $<ds_name>:job.resultCount$ for search metadata. Acceptable static text is commentary without numbers ("The story is margin, not volume") — see splunk-dashboard-interactivity §4.4 and new BAN 13 below

The practical rule: if you need a feature and the exact syntax is not in your hand, move it to SPL or drop it. §1.2 Deference again — a table that loads beats a table with perfect per-cell colors that fails to save.

Choropleth-specific advice: for most SOC/ops dashboards with ≤ 15 countries, a horizontal splunk.bar sorted by value is better information design than a world map. A map is fuzzy (viewer must estimate color darkness → value); a bar chart is precise (viewer reads the number). Recommend a map only when the geographic distribution itself is the insight (e.g., "is this attack regional or global?") — not when the ranking is the insight. Tufte §1.1 Clarity.

2.1 The banned aesthetic patterns

Tell	Why it screams AI	What to do instead
Purple→cyan or purple→blue gradient panel backgrounds	Canonical v0/shadcn default	Solid dark (#101014) or solid light (#F7F7F5) — no gradient
Gradient text on big numbers	"CSS showcase" tell	Solid color, semantic (green/amber/red) or neutral white/black
Glassmorphism / frosted-glass cards	2022 Apple Vision Pro cliché, now AI-default	Opaque cards (#1A1A2E dark / #FFFFFF light) with subtle 1px stroke or no stroke
Every corner rounded to 12+ px	"SaaS rounded" vibe	4–6 px for functional UI; 0 px (square) for data-heavy/editorial feel
All 20 Splunk default colors on one chart	Accepting defaults = AI tell	Max 6 series colors, or 2–3 semantic + seriesColorsByField
Drop shadows on every panel	Material Design cargo-cult	No shadows on data panels. Shadows imply physicality; dashboards are not paper
Emoji or cutesy icons on serious dashboards	Enterprise LLM default	Use Splunk's icon set sparingly, monochrome, same-weight
Bouncy/elastic easing on chart loads	"Impressive animation" reflex	Splunk doesn't do this natively — don't add it via custom CSS either
Rainbow palette on ordered data	Categorical treatment of sequential data	Single-hue gradient (sequential) or diverging (two-hue) for ordered
3D donut charts, gauges that look like car speedometers	"Executive dashboard" stock image	Flat splunk.pie (if ≤5 slices), splunk.markergauge (flat)
Titles like "Security Overview" / "Key Metrics" / "Important KPIs"	LLM boilerplate	Name the question the panel answers
Filler lorem / "Sample" data left in production	Obvious	Use real SPL or explicit `

2.2 The banned layout patterns

• Nested cards within cards within cards. One level of grouping (a splunk.rectangle behind a KPI row) is max. Two levels is a tell.
• Identical card grids. 3×3 of same-size same-color panels = AI default. Vary the hierarchy (see §1.3).
• 12 pie charts. Pie charts are for ≤5 slices. If you need 12 pies, you need 1 splunk.table or a splunk.bar.
• Gauges for everything. Gauges are for thresholded measures (percentage of capacity, latency vs SLA). Not for counts.
• Centered everything. Centered text in every panel + centered KPIs + centered titles → reads as a landing page, not a tool.

2.3 The humanity tells — what makes a dashboard feel crafted

These are the opposite-of-AI signals. Add at least three to every serious dashboard:

• Asymmetric hierarchy. One panel is clearly bigger/louder than the rest. AI-generated layouts tend toward symmetric grids; crafted ones have a hero.
• Restrained color. 1 accent color + semantic trio + 4 neutrals. Nothing else. Ever.
• Micro-copy that sounds like a colleague. "Jumped 12 % vs last Tuesday" beats "Value increased by 12 %."
• A visible opinion. The designer made a choice. Example: "We don't show blocked traffic here because we don't care — investigate at the firewall dashboard." (Delivered as a splunk.markdown sidebar note on an investigative dashboard.)
• Pixel-conscious alignment. All KPI numbers align to the same baseline. All panel tops align to the same y. All gutters are identical.
• Editorial whitespace. More empty space than feels comfortable on the first pass. Confident designs breathe.

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3. The four Couture archetypes (expanded from ds-design-principles)

The companion ds-design-principles skill defines four canonical archetypes (Executive Summary, Operational Monitoring, Analytical Deep-Dive, SOC Overview). This skill adds a fifth, extends each with persona-specific taste notes, and provides Couture-level detail on hierarchy, color, and whitespace.

For each archetype below: audience → key question → hero pattern → layout → palette → typography notes → antipatterns → personality.

3.1 Executive / Board Briefing — The Apple Keynote aesthetic

Audience: CEO, CFO, CISO, board — non-operational, high-stakes, rarely looked at. Key question: "Can I trust that things are running?" Hero pattern: ONE giant headline number at top center, flanked by 2 supporting KPIs. Single trend chart below. Nothing else. Layout (absolute, 1440 × 960):

y=0    [20 px margin]
y=20   [time range picker, 300 px, left] [last-updated timestamp, right, small secondary]
y=80   [big hero card: 1400 × 240 — 1 number, 72–96 px, with one-line context]
y=340  [3 supporting KPIs: 440 × 140 each, 20 px gutters]
y=500  [primary trend chart: 1400 × 360, minimal axis labels, no legend if 1 series]
y=880  [footer: small grey text with owner + last-reviewed date]

Palette: Light theme. Off-white background (#FAFAF7), charcoal text (#1A1A1F), ONE accent color drawn from the company brand. Muted everywhere else. No red unless something is actually wrong. Typography: Generous. Hero number in the biggest size Splunk allows (customFontSize: "96px" via splunk.singlevalue). Panel titles in sentence case, not title case — feels less corporate. Antipatterns: Multiple tabs, dropdown filters, anything requiring interaction. Executives don't click. If they need to click, email them a PDF. Personality: Generous whitespace. Serif accent on the hero label for editorial gravitas — in Dashboard Studio's dropdown, this means Times New Roman on a single splunk.markdown hero caption (never body copy). See §5.2.1.

3.2 SOC Overview — The Bloomberg Terminal aesthetic

Audience: SOC analysts, 24/7 wall display + analyst workstation. Key question: "Where should I look right now?" Hero pattern: Threat counter strip across the top; attack geo map as anchor; severity breakdown and recent incidents flanking it. Layout (absolute, 1920 × 1080 for wall, 1440 × 960 for workstation):

y=0   [input bar: time (auto-refresh 30s), severity, source]
y=60  [KPI strip: 5 numbers — total events, critical, high, unresolved SLA breach, top attacker]
y=220 [left 65% — attack map (choropleth or bubble)] [right 35% — severity pie, ≤5 slices]
y=620 [recent alerts table, full width, 360 px tall, row-colored by severity]

Palette: Dark theme, high-contrast. Canvas #0A0A0E (deeper than the ds-design-principles default — analysts stare at this for hours). Semantic colors tuned for a dark surround: critical #FF4757, high #FF7A45, medium #FFC542, ok #26D07C, info #3B9FFF. Neutral text #E3E3EC (not pure white — pure white vibrates on OLED walls). Typography: Monospaced rendering for numeric density. splunk.singlevalue major values cannot have their font overridden from the visual editor — mitigate by keeping KPIs big (so minor misalignment is invisible) and by putting the event table below with Font = Monospace so columns align. Use Splunk Data Sans on KPI label markdowns and Splunk Platform Mono on markdown rows showing raw counts, IDs, or timestamps. All numbers right-aligned in tables. No ornamentation. (See §5.2.2.) Antipatterns: Dark mode with red backgrounds (causes eye strain after 20 minutes). Blinking animations (analyst fatigue). More than 2 pie charts (pies don't scale in count comparison). Personality: Density is the point. A Bloomberg Terminal is dense because density = authority. Don't apologize for it with whitespace. Compensate with tight, consistent grid alignment and monospaced numbers so the density reads as precision, not clutter.

3.3 NOC / Operational — The airport-departure-board aesthetic

Audience: On-call engineers, NOC staff, real-time monitoring. Key question: "What is burning right now?" Hero pattern: Status tiles with large readable text, one-glance green/amber/red. Secondary time-series below. Layout: Grid layout works here — consistency of tile size is the virtue. 4 columns × 2 rows of service tiles, followed by a full-width incident timeline. Palette: Dark theme. Green/amber/red palette at a saturation high enough to see from 6 meters away. #00E676 (go), #FFB300 (caution), #F44336 (stop). Background #0C0C10. No info-blue here — distracts from state. Typography: Big. Status labels in 24–32 px. Tile numbers in 40–56 px. Use Splunk Platform Sans as the default — it's the theme default and has the best x-height at large sizes. Set label sizes via customFontSize on the markdown panel. Do not switch to Arial "because it's bolder" — the default is strictly better. Antipatterns: Small fonts (unreadable at distance). Fancy charts (engineers glance, then respond). Multi-series stacked bars (cognitive load during incident). Personality: Functional, almost brutalist. Rounded corners belong here — soft 4 px corners make prolonged viewing less harsh. But no shadows, no gradients, no decoration. "Departure board" is the mental model: instantly legible, never pretty for pretty's sake.

3.4 Analyst / Investigation — The editorial long-read aesthetic

Audience: Threat hunters, SIEM analysts, fraud investigators. Use session: 15–90 minutes. Key question: "What is the story this data tells?" Hero pattern: Rich filter bar at top, multi-series time-series as the anchor, detail table at the bottom, distribution charts in the middle. Layout: Use tabs (input.link with token-switched visualizations) to segment: Overview · Drilldown · Entities · Raw. Each tab follows its own internal hierarchy. Palette: Dark theme preferred (long sessions), but use a lower-contrast variant than SOC: #14141C canvas, #D5D5DE primary text. Saturated colors only on data (series palette is deliberately muted — see §4.3 "Investigative palette"). Typography: Denser information, so smaller type is fine: 12–14 px body, 13 px in tables with 1.4 line height. Tabular figures mandatory. Column headers in SMALL CAPS (via markdown ## HEADER and a uniform sans-serif) for scannability. Antipatterns: Flashy KPIs at the top that steal attention from the investigation. Modal dialogs. Autoplay animations. Personality: Dense but organized. Reads like a Financial Times article — lots of information, but structured so the eye knows where to go. Zero decoration. The data IS the personality.

3.5 Business / Sales / Marketing — The magazine cover aesthetic (Couture-only archetype)

Audience: Revenue leader, marketing ops, customer success. Usually shared in Slack or exported to slide decks. Key question: "Is the business healthy and what is the narrative this quarter?" Hero pattern: Single narrative panel at top (either a hero number or a hero trend), then supporting segmentation. Layout (absolute, 1440 × 960):

y=0   [20 px margin]
y=20  [time range picker + "vs previous period" toggle]
y=80  [hero panel: 1400 × 300 — either 1 hero number with MoM/YoY deltas, or 1 full-width trend with annotated events]
y=400 [3 segment tiles — by channel, by region, by product — 440 × 180 each]
y=600 [conversion funnel OR cohort table — 1400 × 300]
y=920 [footer]

Palette: Light theme, warm. Canvas #FAFAF7 (warm ivory, not cold #FFFFFF). Accent single: a confident non-neutral hue (e.g., #0066CC, #E63946, #38A3A5 — one, not three). Semantic for deltas: #2A9D5F for positive, #D62828 for negative (avoid forest-green / fire-engine-red — use slightly desaturated versions so the page feels edited, not alarming). Typography: Personality allowed — but the visual editor only gives you Times New Roman as a serif option. For a marketing-facing dashboard, set Times New Roman on ONE splunk.markdown hero caption for a magazine-feel, and keep body copy in Splunk Platform Sans. Tables stay Proportional here; see §5.3 for the compensating disciplines when you can't afford Monospace. Antipatterns: Too much motion, too many colors, treating a business dashboard like a SOC dashboard. No red flashing. Personality: Confident, edited, narrative. Feels like a page from The Economist charts, not a Grafana default. Annotations (annotationX, annotationLabel on line charts) turning data points into story moments.

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4. The color system — Couture palettes

The biggest single lever for anti-AI design is color restraint. Below are four complete, accessibility-checked palettes. Pick ONE per dashboard. Never mix.

4.0 How to construct a palette (if you must build a custom one)

Splunk Dashboard Studio accepts hex colors only — there is no OKLCH in seriesColors, fillColor, or majorColor. The palettes in §4.1–§4.4 are delivered as hex outputs, but if you need to construct a custom palette (e.g., to graft a corporate brand hue into a Couture system), use these perceptual rules adapted from impeccable's color principles and convert the final values to hex before pasting into JSON.

Principle 1 — Think in OKLCH, publish in hex. Tools like oklch.com and Culori let you design in OKLCH (perceptually uniform — equal lightness steps look equal) then export hex. This produces palettes where "500" and "600" are actually one step apart visually, unlike naive HSL scales where mid-tones collapse.

Principle 2 — Reduce chroma at the extremes. As a color approaches white or black, lower its chroma. A bold blue at 55 % lightness might use chroma 0.15; the same hue as a hover-card tint at 90 % lightness wants chroma ~0.08. High chroma at high lightness looks radioactive, not refined.

Principle 3 — Tint neutrals toward your brand hue. This is the single most effective anti-default trick. A "gray" UI surface that carries a chroma of 0.005–0.010 toward the brand hue creates subconscious cohesion between brand accent and chrome. Pure neutrals (#1A1A1F with zero chroma) feel generic. The Couture palettes below already apply this — note that Obsidian's neutrals lean very slightly blue-cool (#15151C, #26262F), while Warm Editorial's neutrals lean warm-tobacco (#F7F5F0, #6F6B65). This is deliberate.

Principle 4 — The 60-30-10 rule is about visual weight, not pixel count. 60 % neutral / surface, 30 % secondary text and borders, 10 % accent and data. Accents work BECAUSE they are rare. If every panel has an accent stripe and every number is colored, the accent is gone and everything is noise. Count your accents and kill half of them.

Principle 5 — Dark backgrounds want lighter text weight compensation. Light text on dark backgrounds reads as lighter than dark text on light backgrounds at the same weight. Add approximately 0.05–0.1 to your line-height on dark themes, and consider bumping weight by one step (400 → 500) for body text on dark — it reads more confidently without shouting.

Principle 6 — Graft, don't replace. If the company's brand red is #D62828 and your target palette is Obsidian, do NOT rebuild Obsidian around #D62828. Instead, remap Obsidian's semantic-critical value from #FF4757 to #D62828 (keep everything else). The palette stays coherent; the brand lives inside it.

4.1 Palette: "Obsidian" — dark, operational (SOC / NOC default)

Canvas background       #0A0A0E
Panel card fill         #15151C
Card stroke (if used)   #26262F    (1 px max, often omitted)
Primary text            #E3E3EC    (NOT pure white)
Secondary text          #8A8A98
Tertiary / disabled     #55555E

Semantic — critical     #FF4757
Semantic — high         #FF7A45
Semantic — warning      #FFC542
Semantic — ok           #26D07C
Semantic — info         #3B9FFF
Semantic — unknown      #8A8A98

Series palette (6, in order):
  1  #3B9FFF   blue
  2  #FFC542   amber
  3  #26D07C   green
  4  #B084FF   purple
  5  #26E0C8   teal
  6  #FF7A45   orange

Accent (pick ONE for emphasis):
  Cyber cyan             #00D4E1
  Royal violet           #7C4DFF
  Sunset                 #FF6B35

All combinations pass WCAG AA (4.5:1) against the canvas.

4.2 Palette: "Porcelain" — light, editorial (Executive / Business default)

Canvas background       #FAFAF7    (warm ivory, not cold white)
Panel card fill         #FFFFFF
Card stroke (if used)   #E6E4DF
Primary text            #1A1A1F
Secondary text          #6B6B70
Tertiary                #A5A5AA

Semantic — critical     #C0392B
Semantic — high         #D97706
Semantic — warning      #B08600
Semantic — ok           #2A9D5F
Semantic — info         #1E6FBD
Semantic — unknown      #9B9BA0

Series palette (6):
  1  #1E6FBD   steel blue
  2  #D97706   amber
  3  #2A9D5F   forest green
  4  #7C3AED   plum
  5  #0891A5   teal
  6  #B93660   magenta

Accent (ONE):
  Cardinal               #C0392B
  Oxford blue            #0B3D91
  Forest                 #1B5E20

4.3 Palette: "Smoke" — dark, investigative (Analyst default, muted)

Deliberately desaturated so data series never compete with UI chrome.

Canvas background       #14141C
Panel card fill         #1C1C26
Card stroke             #2A2A36
Primary text            #D5D5DE
Secondary text          #888894

Series palette (8, all desaturated):
  1  #7AA2CC   muted blue
  2  #D4A574   muted amber
  3  #7ABFA0   muted green
  4  #B29ED4   muted lavender
  5  #8FCAC4   muted teal
  6  #D4968F   muted coral
  7  #A3A890   muted olive
  8  #BBA6C4   muted plum

Semantic (still saturated for status, unlike the series):
  Critical               #E74C3C
  Warning                #F39C12
  OK                     #27AE60

The whole point of Smoke: the status colors pop against muted data, so the eye goes to severity first.

4.4 Palette: "Warm Editorial" — light, magazine (Business / Marketing)

Canvas background       #F7F5F0    (warm paper)
Panel card fill         #FFFFFF
Card stroke             none (use 24+ px gutters for separation instead)
Primary text            #1A1A17    (warm near-black, not #000)
Secondary text          #6F6B65
Accent label            #9C6B2F    (tobacco — for "live" indicators, sparingly)

Semantic (muted for editorial feel):
  Positive               #2F7A52
  Negative               #B84A3E
  Neutral/reference      #7A7570

Series palette (6):
  1  #264653   deep teal
  2  #E9C46A   mustard
  3  #E76F51   terracotta
  4  #2A9D8F   sea green
  5  #8E6C88   dusty plum
  6  #F4A261   amber

4.5 Palette discipline rules (never violate)

1. Pick one palette. Do not mix palettes. If the user has an existing brand palette, extract 1 accent color from it and graft it into the closest Couture palette — never replace the whole system.
2. Semantic colors are untouchable. Never use red for a non-critical data series, never use green for a non-OK state. Your SOC analyst will associate the color with meaning within 5 minutes and you will mislead them forever.
3. Max 6 data series per chart. Beyond 6, use "Top 5 + Other" or split into multiple charts.
4. Use seriesColorsByField, not seriesColors. The latter is positional and breaks when SPL returns series in different order; the former locks a color to a specific value. Example:

   "seriesColorsByField": {
     "allowed": "#26D07C",
     "blocked": "#FF4757",
     "monitored": "#FFC542"
   }
   

5. Accent color is used at most twice per dashboard. Accent is for the one or two things the eye MUST land on. If everything is accented, nothing is.
6. Verify contrast. Minimum 4.5:1 for normal text against its background, 3:1 for large (≥18pt regular or 14pt bold) text and for essential graphical elements. Test every custom color.
7. Never red/green alone to encode state. Always pair with icon (splunk.singlevalueicon), shape, or text label. 8 % of men have red-green CVD.

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5. Typography — the Couture type system

Splunk Dashboard Studio gives you narrower typography levers than a blank web canvas: a Font family dropdown (7 options) on splunk.markdown, a Font dropdown (2 options: Proportional / Monospace) on splunk.table, and fontSize / customFontSize / fontColor on markdown and single-values. You cannot type custom fontFamily strings from the visual editor. Use what you have deliberately — the constraint is clarifying, not limiting. (See §5.2 for the full option menu and §5.2b for the selection procedure.)

5.1 The type scale (pick from these, do not introduce rogue sizes)

Display (hero KPI)      72  px   /  80 line-height   /  weight 600  /  tracking -1.5 %
Display S (hero alt)    56  px   /  64               /  600          /  -1.0 %
Title L (section)       28  px   /  36               /  600          /   0
Title (panel)           18  px   /  24               /  600          /   0
Title S (subtitle)      14  px   /  20               /  600          /   0
Body L                  15  px   /  24               /  400          /   0
Body                    13  px   /  20               /  400          /   0
Caption                 12  px   /  18               /  400          /   0
Label (small caps)      11  px   /  16               /  600          /  +8 %  TEXT-TRANSFORM: uppercase

Ratio across scale is roughly 1.25 (minor third) — crisp but not aggressive.

5.2 Font-family recipes — the Splunk reality

Splunk Dashboard Studio is a font-constrained environment. You cannot type arbitrary fontFamily strings into the visual editor. The UI only exposes dropdowns, and the dropdowns are surprisingly short. Design within the constraint — do not fight it.

5.2.1 What you can actually choose from

For splunk.markdown panels (the visual editor's "Font family" dropdown):

Schema-locked list — these 7 strings are the ONLY legal values for fontFamily. Splunk's JSON schema rejects anything else at save. There is no "Splunk Data Serif", no "Inter", no "system-ui", no "Menlo", no custom fonts. If you want a serif, you use Times New Roman. If the brand requires a specific custom font, that's an app-level CSS override — out of scope for dashboard JSON.

Option (exact string required)	Category	Couture verdict
Splunk Platform Sans (default)	Sans-serif, UI-chrome	Safe default. Neutral. Don't fight it for most panels.
Splunk Data Sans	Sans-serif, optimized for numbers	Preferred for data-heavy markdown — designed for tabular readability.
Splunk Platform Mono	Monospace	Use for code, IDs, hashes, timestamps in markdown.
Arial	Sans-serif	Never. Generic lazy default. Splunk Platform Sans is strictly better.
Helvetica	Sans-serif	Acceptable but not different enough from Splunk Platform Sans to be worth the switch.
Times New Roman	Serif	The only editorial/serif option available. Use it deliberately for hero captions on executive or business dashboards.
Comic Sans MS	Novelty	Never. Under any circumstances. Including ironic.

For splunk.table (the "Font" dropdown):

Option	Couture verdict
Proportional (default)	Use for text-dominant tables (names, descriptions, labels).
Monospace	Use for any table with numeric columns. Delivers tabular alignment without relying on font-feature-settings. Non-negotiable for KPI-heavy tables.

For single-value components and charts: font family is inherited from the dashboard theme and the splunk.singlevalue component doesn't expose a font dropdown. You can only indirectly influence it via custom app-level CSS (Splunk Enterprise) or the theme editor — treat this as not controllable from the visual editor and plan accordingly. If you need monospaced KPI numbers for alignment, use a splunk.markdown header with "Splunk Platform Mono" above a row of single-values, and accept that the major values themselves will render in the theme's default.

5.2.2 Couture recipes — built from the available options only

Context	Markdown font	Table font	Why
Default / operational	Splunk Platform Sans	Monospace if numeric, else Proportional	Clean, neutral, doesn't fight the data.
SOC / engineering density	Splunk Data Sans for all panels, Splunk Platform Mono for KPI-context headers	Monospace (always)	Data Sans is tuned for scanning numbers. Mono headers reinforce the "terminal" feel.
Executive / board hero	Times New Roman for the hero caption or section header; Splunk Platform Sans for everything else	Proportional	Serif hero label adds editorial gravitas. Do NOT set Times New Roman on body copy — it reads as 1998 corporate memo. Hero only.
Analyst / investigation	Splunk Data Sans for panel titles and markdown notes; Splunk Platform Mono for _raw columns and ID fields	Monospace	Data Sans for scan, Mono for raw. Everything is about reading speed.
Business / magazine	Times New Roman for the top narrative markdown only; Splunk Platform Sans for tile labels and body	Proportional	A single serif gesture at the top reads as "edited", not "corporate". Keep everything else neutral.

5.2.3 The three hard rules

1. Splunk Data Sans is the most under-used option. If your dashboard is data-heavy, switch markdown panels containing numbers or data labels from the default (Splunk Platform Sans) to Splunk Data Sans. It's a free readability win and an anti-default-reflex win simultaneously.
2. Times New Roman is your only serif lever. Use it sparingly and deliberately. One markdown panel per dashboard, usually a hero caption or a section header. Never for body copy.
3. Comic Sans MS and Arial are non-starters. Comic Sans is obvious. Arial is just the lazy default you fell back to when nothing else was available. Since we do have other options, there is no excuse.

5.2b The font-selection procedure (Splunk-constrained)

Context reality check. The impeccable design skill tells you to browse Pangram Pangram, Klim, and Velvetyne to escape training-data default fonts. That advice is correct for web design and useless for Splunk Dashboard Studio. In Dashboard Studio's visual editor, your font-family choice is a dropdown with 7 options for markdown panels and 2 options for tables (§5.2.1). You cannot add fonts. You cannot type a custom string. The impeccable spirit still applies — "do not pick the default out of reflex" — but the mechanics are entirely different.

This is your full procedure. It has 3 steps, not 6.

Step 1 — Write down the 3 concrete tone words (from §0.5.4)

Same step impeccable demands, still the single biggest defense against reflex choice. Before opening the font dropdown, write down three concrete words describing how this dashboard should feel. NOT "modern" or "clean" — use specifics:

• "calm and clinical and careful" → Splunk Platform Sans body, Times New Roman section headers, Proportional tables
• "fast and dense and unimpressed" → Splunk Data Sans everywhere, Monospace tables, no serif anywhere
• "warm and editorial and confident" → Splunk Platform Sans body, Times New Roman hero caption, Proportional tables
• "brutalist and terminal and precise" → Splunk Platform Mono for headers, Splunk Data Sans for body, Monospace tables

The three words constrain the dropdown choice. Don't open the dropdown until the words are written.

Step 2 — Reject the default out of reflex

The visual editor pre-selects Splunk Platform Sans for markdown and Proportional for tables. These are safe and neutral. They are also what every untouched dashboard uses. If you leave them selected without thinking, you're accepting the template.

Rules for switching away from defaults:

• For any markdown panel containing numbers or data labels: switch to Splunk Data Sans. It's the whole reason Splunk ships two sans fonts. Use it.
• For any hero caption, section header, or editorial flourish on light-theme dashboards: consider Times New Roman. Exactly once per dashboard, at the top or as a section marker.
• For any table with a numeric column: switch to Monospace. No exceptions. If you've ever tried to scan a column of currency values in a proportional font, you know why.
• For any panel containing code, hashes, IDs, or fixed-width content: switch to Splunk Platform Mono in markdown; Monospace in tables.

Rules for NOT switching:

• Don't switch to Arial. It's a worse Splunk Platform Sans.
• Don't switch to Helvetica. It's an alias of Arial on most systems and doesn't meaningfully differ from Splunk Platform Sans to the eye.
• Don't switch to Comic Sans MS. Ever. Not ironically. Not for a "fun" dashboard. Not at all.

Step 3 — Document the choice in the handoff brief

When handing off to splunk-dashboard-studio, be explicit about every font-family assignment:

FONT ASSIGNMENTS
  Hero markdown caption      : Times New Roman
  Section header markdowns   : Splunk Data Sans
  KPI label markdowns        : Splunk Data Sans
  Body-text markdowns        : Splunk Platform Sans
  Code / ID markdowns        : Splunk Platform Mono
  All tables                 : Monospace (KPI-heavy) or Proportional (text-heavy)

Five lines. Done. No Inter, no JetBrains Mono, no Georgia, no fallback chains — those are web-design artifacts that don't apply here. If you write a handoff that says "fontFamily: 'Inter', system-ui, ..." the syntax skill will try to set that on a component that doesn't accept custom strings, and it will silently fall back to the theme default. Stay inside the dropdown.

5.2c What about custom fonts?

Splunk Enterprise with custom app-level CSS, and in some Splunk Cloud setups, allow you to inject CSS that overrides component fonts with web-hosted alternatives. If you have this level of control and a branded need (executive dashboard rendered to PDF for a board meeting, marketing dashboard embedded in a customer portal), you can load a custom font via CSS and override the theme.

But — unless you have a concrete branded reason, don't. The reasons:

1. The rendered font must be installed on the viewer's browser or web-hosted reliably. A broken fallback looks worse than Splunk Platform Sans.
2. It doesn't apply inside the visual editor — you still see the default in edit mode and only the custom font in view mode. This surprises non-authors who edit the dashboard later.
3. Splunk Cloud has progressively restricted custom CSS. Something that works today may not work after a cloud upgrade.

If you do go custom, apply the impeccable font-selection procedure: 3 tone words, reject the reflex list (Inter, IBM Plex, DM Sans, Fraunces, etc.), shop at Google Fonts / Pangram Pangram / your brand CDN. But 95 % of Splunk dashboards should stay inside the 7 + 2 default options. Constraints are good. They eliminate the font-picking rabbit hole and let you focus on hierarchy, color, and layout — which are where dashboards actually win or lose.

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5.3 Tabular figures — MANDATORY for numbers

Every number that appears next to another number (column total vs row total, KPI row, table) must be tabular — meaning each digit occupies the same horizontal space so columns align. Misaligned numbers read as amateur. Aligned numbers read as precise.

The Splunk Dashboard Studio solution is simpler than the impeccable / web solution. You do not need font-feature-settings: 'tnum'. You do not need to hunt for fonts that ship tabular figures by default. The platform gives you direct monospace options:

Component	How to force tabular alignment
splunk.table with numeric columns	Set the Font dropdown to Monospace. Done. Every digit aligns because every glyph is fixed-width.
splunk.markdown panels displaying a number	Set the Font family dropdown to Splunk Platform Mono. Every digit aligns.
splunk.markdown displaying labels next to data	Splunk Data Sans — designed by Splunk for tabular number rendering inside a proportional sans. Second-best option if Mono feels too technical.
splunk.singlevalue KPI major values	Font is inherited from the theme and cannot be changed from the visual editor. You cannot force tabular. Mitigate by: (a) grouping KPIs so each gets its own column (numbers don't need to align across KPIs if there's visible space between them), (b) showing large single numbers (tabular matters less at 72 px than at 14 px), (c) using a splunk.table instead of a KPI row when horizontal alignment is critical.

When table Monospace is too aggressive. Monospace tables look "coder-y" and can clash with an executive or marketing palette. For those contexts, leave the Font at Proportional and compensate by: (a) right-aligning numeric columns (so at least the ones digits line up), (b) formatting numbers with consistent precision (always 2 decimals on currency, always 0 on counts), (c) using the thousands separator. Three disciplines together get you 80 % of the Monospace benefit without the aesthetic cost.

Deep customization path (rarely worth it). If you ship a custom Splunk app with app-level CSS, you can inject font-variant-numeric: tabular-nums to force Splunk Platform Sans to render tabular digits (it supports the tnum OpenType feature). The CSS pattern is:

.dashboard-panel .splunk-number,
.single-value-panel .major-value,
.data-table td.numeric {
  font-variant-numeric: tabular-nums;
  font-feature-settings: 'tnum' 1;
}

But unless you have a specific need that the Monospace / Splunk Platform Mono / Splunk Data Sans options cannot solve, don't reach for custom CSS. The built-in options cover the 95 % case. The last 5 % — KPI major values — is a platform limitation, not a design failure.

5.4 Title discipline (repeat until internalized)

• 3–5 words maximum.
• Title Case for operational / SOC / NOC dashboards (feels authoritative).
• Sentence case for executive / business dashboards (feels edited).
• No subtitles unless the metric is genuinely ambiguous.
• No emojis. Ever. (Unless the brand explicitly requires one — then ONE, consistent, on the header only.)
• Answer a question: "Failed Logins — Last Hour", not "Login Chart".
• No "Dashboard" in titles. We know it's a dashboard.

5.5 Number formatting rules

• Always show the unit (%, ms, GB, requests/s). Never make the viewer guess.
• Thousands separator for values > 999. Set "thousandSeparated": true in columnFormat.
• Precision: exactly as much as matters. Currency: 2 decimals. Percentage: 0–1 decimal. Counts: 0. Latency: 0 decimals if ms < 10000, else convert to seconds with 1 decimal. Never show $3,848,305.93 on a dashboard.
• Big numbers: abbreviate above 10,000 with 1 decimal (12.4K, 3.2M, 1.8B). Use "yAxisAbbreviation": "auto" on axes.
• Deltas / trends: always include sign and unit. +12.4 %, not 12.4.
• Timestamps in tables: convert from epoch to "%b %d, %H:%M" via | eval _time=strftime(_time,"%b %d, %H:%M"). Drop the year unless the time range spans it.

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6. Layout & spacing — the 8-point Couture grid

6.0 Absolute layout is the Couture default — this is non-negotiable

Always use "type": "absolute" for dashboards that claim design intent. "type": "grid" is a convenience layout — it auto-stacks panels in a responsive 12-column flow. It is the default that the visual editor drops you into, and it is the single biggest reason Splunk dashboards look AI-generated: every panel is the same width, every row is the same height, hierarchy collapses into a uniform tile-field.

Couture dashboards live in absolute layout because:

1. Pixel-exact hierarchy. You cannot build an F-pattern, a hero card, an editorial asymmetric composition, or a two-column narrative in grid. You get equal-width cells and equal-height rows. Grid is designed for people who don't want to design.
2. Deliberate whitespace. §6.5's 24 px / 32 px / 80 px rules only hold when you place panels explicitly. Grid gives you 8 px gutters and never more.
3. One big panel next to three small ones. The single most effective layout gesture in dashboards — hero + supporting trio, or wide map + narrow KPI stack — is impossible in grid without hacking cell spans.
4. Alignment across panels of different types. Grid aligns boxes. Absolute lets you align the value inside the box to a neighbouring value inside a different type of box. This is where a dashboard goes from "arranged" to "composed".
5. Reproducibility across viewers. Absolute with display: "auto-scale" scales cleanly down from 4K to laptop. Grid reflows, which destroys the composition you worked on.

When grid is acceptable — the narrow exception list:

• Pure "table of charts" utility pages — e.g., a per-service error-rate wall where all 24 services must be shown as identical small multiples and the point is uniformity, not hierarchy. This is the only case.
• Internal admin pages and dev tooling where nobody claims design intent.
• The non-hero tabs of a tabbed dashboard if they are purely reference lookups. (The hero tab must still be absolute.)

When asked to design, always specify absolute in the brief. When reviewing an existing dashboard, the first question is "is this grid or absolute?" — if grid, the design work hasn't started yet. The JSON shape lives in splunk-dashboard-viz §18; Couture's only position is: pick absolute.

The one-line Couture doctrine: grid is for prototypes, absolute is for shipping.

6.1 The grid (the 8-point measurement system, not the layout type)

Every dimension is a multiple of 8 px. Gutters, margins, panel sizes, paddings — all multiples of 8. This is the measurement grid — independent of and complementary to choosing "type": "absolute" in the JSON. The 8-point discipline is what makes absolute layouts look intentional rather than sloppy.

Common canvas sizes that work with the grid:

• 1440 × 960 (workstation)
• 1920 × 1080 (NOC wall)
• 2560 × 1440 (4K wall)

6.2 Spacing system (use these values, no others)

2 px     hairline    (internal padding on chart borders only)
8 px     xs          (icon-to-text, label-to-value)
16 px    s           (internal panel padding, small gutters)
24 px    m           (default gutter between panels)
32 px    l           (section-to-section)
48 px    xl          (hero padding — above a hero KPI card)
80 px    xxl         (canvas margin on wall displays)

6.3 Panel minimums (smaller = unreadable)

Panel type	Min width × height	Comment
Single value	240 × 120	Below this, major value shrinks to unreadable
Single value hero	440 × 200	For executive dashboards
Line / area / column	400 × 240	Below 240 height, axis labels crush
Bar (horizontal)	400 × 200 + 24 px per bar	Height scales with count
Pie	240 × 240	Square minimum
Table	480 × 200	Below this, columns truncate
Map	600 × 400	Smaller loses detail
Timeline / Sankey / linkgraph	640 × 360	Anything less is illegible
Markdown header	full width × 48	Section markers

6.4 F-pattern reading order

Users scan top-left first, then drift right, then drop to next row, then right again, in an "F" shape. Place importance accordingly:

• Top-left: time-range picker + the single most important KPI.
• Top-right: the secondary KPIs, last-updated timestamp.
• Middle-left: the primary chart that supports the top-left KPI.
• Middle-right: the secondary chart or distribution.
• Bottom: detail tables, event streams, logs.

6.5 Whitespace rules

• Every panel edge: 24 px minimum to any neighbor.
• Every canvas edge: 32 px minimum (80 px on wall displays).
• Inside a KPI grouping card (splunk.rectangle background): 16 px between the card edge and the first/last KPI edge.
• Above section headers (markdown): 32 px.
• Below section headers: 16 px.

If two panels are closer than 16 px, they read as one panel. This is sometimes desired (grouping), but make the choice deliberate.

6.6 The editorial whitespace trick

Confident designs leave more empty space than feels comfortable. Specifically: on executive / business dashboards, leave one grid cell empty somewhere visible. Not every inch has to be filled. Negative space is expensive — using it signals that you had the confidence not to fill it with garbage.

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7. Dashboard Studio-specific Couture tricks

These are things you can only do if you know the Splunk Dashboard Studio JSON well. They separate pro work from default-accepted work.

7.1 The "hero number with context" pattern

Not just a number — a number with comparison, trend, and qualitative color.

"viz_hero": {
  "type": "splunk.singlevalue",
  "title": "Critical Alerts",
  "dataSources": { "primary": "ds_critical_count" },
  "options": {
    "majorValue": "> primary | seriesByName('count') | lastPoint()",
    "trendValue": "> primary | seriesByName('count') | delta(-2)",
    "trendDisplay": "percent",
    "sparklineValues": "> primary | seriesByName('count')",
    "sparklineDisplay": "below",
    "unit": "",
    "majorColor": "> majorValue | rangeValue(statusColors)",
    "backgroundColor": "transparent",
    "customFontSize": "72px"
  },
  "context": {
    "statusColors": [
      {"value": "#26D07C", "to": 1},
      {"value": "#FFC542", "from": 1, "to": 10},
      {"value": "#FF4757", "from": 10}
    ]
  }
}

Notes: backgroundColor: "transparent" drops the default Splunk card chrome so the number sits on the dashboard canvas. Combine with a splunk.rectangle BEHIND the value for a deliberate card, or leave transparent for the minimalist "number on canvas" look.

7.2 The "card-as-rectangle" trick for grouping without chrome

Instead of letting each panel draw its own default card, disable each panel's chrome and put a splunk.rectangle behind a group. This gives you one clean background for a group of related KPIs:

"viz_kpi_group_bg": {
  "type": "splunk.rectangle",
  "options": {
    "fillColor": "#15151C",
    "fillOpacity": 1,
    "strokeWidth": 0,
    "cornerRadius": 6
  }
},
"layout": {
  "structure": [
    {"item": "viz_kpi_group_bg", "position": {"x":40,"y":80,"w":1360,"h":160}},