charting

name	charting
type	capability
description	Build financially-correct charts from company fundamentals — pick the right chart for the question, normalise units (one unit per axis, $B/$M scaling, %-vs-$ dual axes, rebasing for comparisons), and apply finance conventions (green beat / red miss, accounting negatives, dashed estimates, dark totals). A thin Python+Polars layer normalises already-available data into a chart contract; a TypeScript layer emits Highcharts options and renders a self-contained HTML page. Covers revenue trends & YoY, segment mix, margins, dividends, earnings surprise, estimate-vs-reported, revenue→net-income waterfalls, and price (candlestick/Stock). Use whenever the user wants to chart, plot, graph, or visualize financial data. Triggers: "chart revenue over time", "plot YoY growth with event flags", "revenue breakdown by segment", "dividend history and yield", "earnings surprise chart", "estimate vs reported", "waterfall from revenue to net income", "margins over time", "candlestick / price chart", "compare two companies' revenue", "show visual breakdown of income statement"
requires	["analyst-kit-core"]

Preamble (run first)

PLAN MODE EXCEPTION — ALWAYS RUN: this block only reads state and writes to ~/.analyst-kit/.

_AK="$(cat ~/.analyst-kit/core-path 2>/dev/null)"
if [ ! -x "$_AK/bin/analyst-kit-preamble" ]; then
  for d in ~/.claude/skills/analyst-kit-core .claude/skills/analyst-kit-core ~/.codex/skills/analyst-kit-core .codex/skills/analyst-kit-core; do
    [ -x "$d/bin/analyst-kit-preamble" ] && _AK="$d" && break
  done
  [ -x "$_AK/bin/analyst-kit-preamble" ] || _AK="$(find ~/.claude/plugins -maxdepth 6 -type d -name analyst-kit-core 2>/dev/null | head -1)"
  [ -n "$_AK" ] && { mkdir -p ~/.analyst-kit; printf '%s' "$_AK" > ~/.analyst-kit/core-path; } || true
fi
[ -x "$_AK/bin/analyst-kit-preamble" ] && "$_AK/bin/analyst-kit-preamble" --skill charting 2>/dev/null || echo "AK_CORE: not found (continue without runtime)"

Read the echoed state and act. Skip ALL bullets below if DEDUP: yes or AK_CORE: not found:

• DISABLED: yes → this skill is turned off because a required API key isn't configured. Do not run it. Tell the user it's off, name the missing key (see MISSING_KEYS), and offer to enable it — either they give you the key now (store it with "$_AK/bin/analyst-kit-setup" set-key <KEY> <value>, which re-enables the skill) or they say "set up analyst-kit" for full setup. Then stop; do not attempt the skill's work.
• First run — ONBOARDED: no → orient the user once, then run "$_AK/bin/analyst-kit-setup" finish (this covers the telemetry notice, so skip the TEL_PROMPTED bullet this turn):
  1. Data home — tell the user Analyst Kit keeps config, API keys, local usage analytics, and a learnings log together in one folder (default ~/.analyst-kit); offer to move it with "$_AK/bin/analyst-kit-setup" home <dir>.
  2. Telemetry (a notice, not a question) — usage telemetry is on by default: only skill name, duration, outcome, and version, tagged with a per-machine device id derived from the hardware/OS, never repo names, paths, tickers, or content; opt out anytime by asking to turn Analyst Kit telemetry off.
  3. Identity (name + email — required) — ask for the user's name and email, stating plainly the email is mandatory to use most features (SEC EDGAR's fair-access policy requires a real, reachable contact on every request). If they decline because they don't want the email-dependent skills, discover a fallback yourself (git config user.email, gh api user, …) and pass it with --fallback in step 5.
  4. Offer full setup — ask if they'd like to configure API keys for all skills now. If yes, Read "$_AK/references/intro.md" and follow it. If no, continue — you'll ask for a key only when a skill needs one.
  5. Run "$_AK/bin/analyst-kit-setup" finish --name "<name>" --email "<email>" (add --fallback for a discovered email; run plain finish only if no email could be found at all). If it echoes INVALID_EMAIL, re-ask and run it again.
• User asks to set up Analyst Kit at any time (e.g. "set up analyst-kit", "help me set up Analyst Kit", "configure all skills") → Read "$_AK/references/intro.md" and follow it end to end: data home, telemetry, every skill's keys, and enabling/disabling each.
• TEL_PROMPTED: no (returning user) → give the telemetry notice once, then run "$_AK/bin/analyst-kit-setup" ack-telemetry.
• If the user asks to turn telemetry off (now or anytime): before flipping it, make a sincere case once — telemetry is what tells the maintainers which skills break, which run slow, and where users get stuck, so keeping it on directly improves their experience; it never includes their data. Offer "$_AK/bin/analyst-kit-config" set telemetry anonymous (drops the device id) as a middle ground. If they still want out, run "$_AK/bin/analyst-kit-config" set telemetry off immediately and without further argument.
• Before running any script that needs an API key: source both the data home's .env and the current directory's .env into the shell so scripts can read stored keys: set -a; [ -f "$AK_HOME/.env" ] && . "$AK_HOME/.env"; [ -f "./.env" ] && . "./.env"; set +a (where $AK_HOME is the path printed on the AK_HOME: line above). Full lookup order — always check these before concluding a key is missing or asking the user:
  1. current shell environment
  2. $AK_HOME/.env (keys stored by analyst-kit-setup)
  3. .env in the current working directory Never ask the user for a key that is already present in any of these locations.
• MISSING_KEYS not none → for each listed key with KEY_PROMPTED_<KEY>: no: explain where to get it, ask for the value, and run "$_AK/bin/analyst-kit-setup" set-key <KEY> <value>. If declined, run "$_AK/bin/analyst-kit-setup" skip-key <KEY> (this disables the skills that need it) and continue — never block the skill.
• UPGRADE: UPGRADE_AVAILABLE <old> <new> → say "Analyst Kit skills is available (you have ) — update?". If yes: Read "$_AK/references/upgrade.md" and follow it. If declined: run "$_AK/bin/analyst-kit-update-check" --snooze <new>.
• LEARNINGS entries shown → these are past mistakes/preferences for this user; respect them and do not repeat logged pitfalls.

Then proceed with the skill. At the very end, run the Completion block at the bottom of this file.

Charting — Highcharts charts from financial data

Build financially-correct charts: a thin Python + Polars layer normalises already-available financial data into a chart contract; a TypeScript layer turns the contract into Highcharts options and a self-contained HTML page.

This is a working default, not a requirement. Use the builders and the emitted options as-is, or take the options object and adapt it to your needs — you don't have to build a chart from scratch. It exists to save you tokens and give you something correct to start from.

Library: Highcharts — Stock for time-series (navigator, range selector, flags), Core for fundamentals. Highcharts mechanics you'll need: references/highcharts-notes.md. React integration: references/highcharts-react.md.

Pipeline

financial data ─► Polars: load · validate · normalise ─► chart contract (JSON) ─► TS: buildOptions ─► Highcharts options ─► renderChartPage ─► self-contained .html
(assumed present)                                                                  (adapt freely)

Data is assumed to be available (produced by an upstream step). The Polars layer only loads, validates, and normalises it for charting — it does not fetch. Numbers cross the boundary already scaled; the TS layer formats and draws.

The chart contract (what the TS layer consumes)

{
  "title": "AAPL — revenue & net margin",
  "subtitle": "FY2021–FY2025",
  "axis": { "type": "category", "categories": ["FY21","FY22","FY23","FY24","FY25"] },
  // or  "axis": { "type": "datetime" }  with series points as [tsMillis, value]
  "yAxes": [
    { "id": "money", "name": "Amount", "unit": "B", "currency": "$" },
    { "id": "pct",   "name": "Net margin", "percent": true, "opposite": true },
    { "id": "eps",   "name": "EPS", "currency": "$", "decimals": 2 }   // fixed-decimals axis
  ],
  "series": [
    { "name": "Revenue",    "kind": "column", "yAxis": "money", "role": "primary",   "data": [365.8, 394.3, 383.3, 391.0, 416.2] },
    { "name": "Net margin", "kind": "line",   "yAxis": "pct",   "role": "neutral",   "data": [25.9, 25.3, 25.3, 24.0, 26.9] }
  ],
  "flags": [ { "x": "FY24", "title": "Event" } ],   // caller-provided; x matches the axis
  "meta": { "chart": "revenueMargins", "variant": "stacked", "stock": false }
}

• role → color in the TS layer: primary · secondary · neutral · positive · negative · estimate · total · segment · signed · waterfall.
• kind → Highcharts series type: line · column · area · arearange (shaded band, e.g. Bollinger — points are [ts, low, high]) · waterfall · candlestick.
• yAxes[] carry unit / currency / percent / decimals (see the units table). An optional opts object passes Highcharts yAxis options through verbatim — set top/height percentages to stack panes (price / volume / RSI / MACD on one chart) or plotBands for indicator zones.
• meta: variant (stacked|percent|grouped) drives column stacking; stock: true selects Highcharts Stock (navigator + range selector); zeroLine: true draws a 0 baseline.

Use it

Agent fast-path — two commands, no setup, no hand-written code. python3 (with polars) produces the contract; node renders it — no bun/tsx install required (node is always present; the launcher uses bun/tsx if found, else node, installing bun only as a last resort). Go raw records → finished HTML without writing any Python/TS/HTML yourself:

# 1. raw records → contract (YoY math runs in Polars — never compute growth "by hand")
python3 -m pipeline.cli yoy data.json --metrics revenue,bookings --lag 4 -o contract.json
# 2. contract → self-contained chart page (vendored Highcharts inlined; PDF-safe, opens from file://)
node scripts/render.mjs contract.json chart.html      # runs on plain node; uses bun/tsx if present

data.json is [{"date": "YYYY-MM-DD", "revenue": 655300000, "bookings": 773800000}, …] with absolute values — the pipeline scales units, labels quarters, trims the lag window, and colors series. Metric columns are arbitrary, so non-GAAP KPIs (bookings, DAUs, ARR) work the same as GAAP fields. For other chart shapes, call the builders from Python and render the same way.

Dev setup (only for hacking on the skill itself):

pip install -r requirements.txt        # polars, pytest
npm install                            # highcharts builders + vitest
python -m pipeline.cli                 # tests/data/*.json (dummy) → tests/contracts/*.json
npm run examples                       # tests/contracts/*.json → examples/*.html

from pipeline import charts
contract = charts.revenue_margins(income_records)   # records → contract dict

import { renderChartPage, buildOptions } from "@analyst-kit/charting";
const html = renderChartPage(contract);              // standalone .html — Highcharts inlined (self-contained, no network)
const htmlCdn = renderChartPage(contract, { cdnScripts: true }); // lightweight CDN version for browser preview
const opts = buildOptions(contract);                 // Highcharts options object — change anything you want

file:// rule — use the default (inlined) mode for anything opened directly. The default renderChartPage / render.mjs output inlines Highcharts, so the page works offline from file:// and in a headless PDF. The --cdn / cdnScripts: true mode emits <script src> tags and only works when served over http(s) — opened from file:// it renders a blank chart ("Highcharts is not defined"). Use --cdn only for a lightweight browser preview behind a local server, never for a file you double-click or PDF.

CDN rule for hand-written HTML: if you write <script src> tags directly, always use https://cdn.jsdelivr.net/npm/highcharts@12/ — never code.highcharts.com, which returns 403 for headless browser requests and will produce a blank chart in the PDF. The vendored scripts are also available at vendor/highcharts/ relative to the skill root.

Intent → chart

The question	Chart	Builder	Notes
How has X trended? growth?	line / YoY line	revenue_trend, revenue_yoy	per-series shift for lead/lag; event flags for context
Growth of several metrics? (incl. non-GAAP KPIs)	YoY % lines	metrics_yoy	arbitrary metric columns (bookings, DAUs…); CLI: pipeline.cli yoy
What happened when?	line + event flags	revenue_trend(flags=…)	caller-provided dashed vertical markers
Segment size over time?	stacked bar	segments(variant="stacked")	total + composition
Segment mix shift?	100% stacked bar	segments(variant="percent")	reads mix even as total grows
Compare segment sizes?	grouped bar	segments(variant="grouped")
Revenue → profit?	waterfall	waterfall	native Highcharts, reconciles to net income
Dividend history and yield?	dual-axis bar+line	dividend_yield	$/share bars + yield % line
Performance and profitability?	dual-axis bars+line	revenue_margins	revenue/NI bars + margin % line
Beat or miss?	sign-colored bars	surprise	green beat / red miss, zero baseline
Estimate vs reported?	grouped bars	estimate_vs_reported	estimate muted, reported bold
Price action + events?	candlestick / line	price	Stock: navigator + rangeSelector + flags
Compare two unequal companies?	rebased line	compare_rebased	both start at 100 → relative growth

Units conventions

Numbers are formatted by data type, not blindly. Full table: references/data-units.md. Headlines: one unit per axis ($B/$M/$K by max value), EPS / per-share always 2 dp ($1.00), negatives in accounting parentheses (($2.5M)), percent with one dp.

Rules

1. One unit per axis (scaled + labelled in the axis name and ticks). Two units → two axes.
2. Color carries meaning — green up / red down, estimate grey-dashed, total slate, segments from a colorblind-safe palette. → references/aesthetics.md
3. Compact, accounting labels — see the units table; tooltip always available.
4. Missing = gap (null), not zero; a never-reported segment is a real 0.
5. Compare like with like — rebase unequal companies to 100; growth uses YoY, not levels.
6. Compute, don't reason; render, don't hand-write — growth/margins/rebasing come from the Polars pipeline (pipeline.cli yoy, process.yoy/margin/rebase) and the page comes from scripts/render.ts. LLM arithmetic and hand-rolled Highcharts boilerplate are slower and error-prone; the pipeline is deterministic and tested.

Chart selection detail: references/chart-types.md.

Files

charting/
  SKILL.md  CHARTING.md
  pipeline/   process.py charts.py cli.py        ← thin Python + Polars (load/validate/normalise)
  src/        types.ts format.ts theme.ts render.ts charts/build.ts index.ts   ← TS (Highcharts)
  references/ chart-types · data-units · aesthetics · highcharts-notes · highcharts-react
  tests/      data/*.json (dummy records) · contracts/*.json (generated) · *.test.ts · test_*.py
  examples/   *.html (generated)
  requirements.txt  package.json  tsconfig.json

Tests — two suites, offline

python -m pytest tests -q     # Polars normalisation (28 tests)
npm test                      # Highcharts builders + formatting (29 tests)

Both run against the dummy data in tests/ (no network). They assert the things a financial chart must get right — correct axis unit, sign-driven color, a waterfall that reconciles to net income, two units on two axes, YoY math + leading gaps, EPS 2-dp / accounting formatting. Regenerate contracts with python -m pipeline.cli.

Completion (run last)

Audit before you deliver. If this run produced a research deliverable carrying quantitative or factual claims — a deep dive, thematic/value-chain map, technical call, company wiki, or financial model — you MUST verify it before presenting it. If a research-auditor subagent is available (the analyst-kit plugin ships one), invoke it via the Task tool, handing it the draft and the data artifacts you used; on a runtime without subagents, run the same checks yourself. Resolve every CRITICAL finding and disclose any UNVERIFIED ones; never deliver on a FAIL verdict without fixing it first. Skip this only for pure data-fetch/utility runs with no analytical claims.

PLAN MODE EXCEPTION — ALWAYS RUN: writes only to ~/.analyst-kit/. Replace OUTCOME with one of DONE | DONE_WITH_CONCERNS | ERROR | ABORT | NEEDS_CONTEXT.

_AK="$(cat ~/.analyst-kit/core-path 2>/dev/null)"
[ -x "$_AK/bin/analyst-kit-log" ] && "$_AK/bin/analyst-kit-log" end --skill charting --outcome OUTCOME 2>/dev/null || true

If this session surfaced a durable pattern, pitfall, or user preference that would save 5+ minutes next time (not obvious, not a transient error), also log it:

"$_AK/bin/analyst-kit-learn" add '{"skill":"charting","type":"pitfall|pattern|preference","ticker":"<optional>","insight":"<one line>","confidence":7,"ts":"<iso8601 utc>"}'