sap-architecture

name

sap-architecture

description

Use this skill WHENEVER the user wants to create, generate, draw, design, or author an SAP architecture diagram, SAP BTP solution diagram, SAP Cloud Foundry / Kyma / ABAP environment landscape, Cloud Connector topology, SAP S/4HANA landscape, Fiori / SAP Build / Joule architecture, subaccount diagram, MCP-to-SAP deployment diagram, XSUAA auth flow, Principal Propagation diagram, or anything that should match the visual style of https://architecture.learning.sap.com / SAP Architecture Center. Input is a text description of the topology; output is a pixel-polished `.drawio` file (and optionally a PNG export) that matches the canonical SAP Horizon look — correct palette, Helvetica typography, 10-px grid, SAP BTP service icons, straight arrows, no clipped labels.

SAP Architecture Diagram

Take a natural-language description of an SAP / BTP / on-prem landscape and produce a polished draw.io file in the SAP Architecture Center visual style. Every artifact it emits is validated against the same rules SAP follows in the published reference architectures.

STOP — read this before generating any XML

This skill normally starts from a pristine SAP reference template. The single most common failure mode is the LLM trying to write a .drawio file from scratch and ending up with: dark page background, custom flow verbs (PROMPT/ROUTE/CONTEXT/DELEGATE), wrong zone hierarchy (e.g. Joule nested inside BTP instead of beside it), missing SAP footer/logo branding, off-vocabulary connector colors. None of those mistakes are recoverable by autofix — they are baked into the structure.

The mandatory first action — before any other tool call — is:

python3 .claude/skills/sap-architecture/scripts/scaffold_diagram.py \
  "<the user's full request, verbatim>" \
  --include-external-sap-references \
  --out <destination.drawio>

That script ranks the 71 bundled SAP templates and, when present, cached official SAP reference architectures against the request, copies the best match to the destination, and prints the alternatives. Now you have a SAP-anchored starting point. From here you make surgical label changes only — never cat <<EOF > foo.drawio, never write XML from scratch.

If the user asks "use the X template", pass --template ac_X.drawio to the scaffold instead. If you genuinely need to inspect candidates first without copying, pass --dry-run.

If the scaffolded family is visibly wrong and no SAP reference is close enough, use render_semantic.py as a constrained fallback for supported archetypes (security-operations, devops, on-prem-connectivity, private-connectivity, btp-application, data-integration, integration-flow, ai-agent). This is still deterministic SAP-style XML, not freehand XML.

The validate.py / compare.py gates will reject weak generations: dark pageBackgroundColor is now an error, novelty pill verbs are warnings, missing zones lower the score against the chosen reference, and all bundled references must score 100 against themselves.

When to use

Trigger on any of:

• "Create an SAP architecture diagram for …"
• "Draw my BTP deployment"
• "Diagram the XSUAA auth flow"
• "Show how ARC-1 connects on-prem SAP via Cloud Connector"
• "Make an L0/L1/L2 SAP ref-arch for …"
• "Like the SAP Architecture Center style"

For generic diagrams (flowcharts, ER, class) without an SAP angle, use the general drawio skill instead.

The 6-step workflow

Follow this sequence exactly — each step produces input for the next, and each gate catches different classes of bug.

1. Parse the description → plan

Before touching XML, write out (in your head or as a hidden scratch pad):

1. Level — pick L0 / L1 / L2. Default is L2. See references/levels.md for signals. SAP's published BTP guideline defines these three levels; do not invent L3 unless the user explicitly asks for a non-SAP internal physical diagram.
2. Zones — list the landscape columns needed, typically 2–4 of: User / MCP Client, SAP BTP, On-Premise, Third-party / Hyperscaler. Some scenarios (Agentic AI) put Joule as its own top-level zone beside BTP, not nested inside.
3. Services — for each zone list the concrete cards (service name, role, vendor). Flag which BTP services need the official icon from the bundled library.
4. Flow — number the steps 1..N. Pick a pill color per step from the semantic palette (auth=green, trust=magenta, MCP=teal, authz=indigo). Use only canonical pill verbs: TRUST, Authenticate, Authorization, A2A, MCP, ORD, HTTPS, OData/REST, SAML2/OIDC, Identity Lifecycle, etc.
5. Accent / focus app — the "star" of the diagram (ARC-1, Joule, user's own app). Uses the purple accent.

Good user context includes: target audience/level, actors and entry points, SAP BTP services, SAP cloud/on-prem/third-party systems, identity and trust mechanism, numbered flow/protocols, required zones, and explicit exclusions. If the user pasted a long architecture note, reduce it to one diagram scope before selecting a template. Do not try to draw every component mentioned in a long document.

Keep this plan short — a 10-line bullet list is plenty. Don't skip it: diagrams built without a plan drift off-grid and end up with bent arrows. The plan is what you feed into scaffold_diagram.py in step 2.

2. Scaffold from a SAP reference template — MANDATORY

This step is non-negotiable. Run scaffold_diagram.py — it both ranks templates and copies the best one to the destination:

python3 .claude/skills/sap-architecture/scripts/scaffold_diagram.py \
  "<the user's full diagram request>" \
  --include-external-sap-references \
  --out <destination.drawio>

If you only want to inspect candidates first, add --dry-run (no file is created). To pin a specific template, use --template <filename>. To rename the <diagram name> attribute after copy, pass --diagram-name "Agentic AI on BTP". The external-reference flag is safe when no external corpus is cached; it silently uses only bundled templates.

71 reference templates are bundled, all Apache-2.0, sourced verbatim from SAP/btp-solution-diagrams (prefix btp_), SAP/architecture-center (prefix ac_), and curated external SAP reference examples (prefix ext_). Reference families: Task Center, Build Work Zone, Build Process Automation, Cloud Identity Services / IAM, Private Link, Event-Driven Architecture, E2B connectivity, multi-region resiliency, Federated ML, hyperscaler data integration, Generative AI / RAG, A2A / MCP, Edge Integration Cell, Business Data Cloud, OData via App Router / CAP, B2B / A2A / API-managed integration, DevOps, Joule, SIEM/SOAR, SuccessFactors integration, and Agentic AI.

The selector reads assets/reference-examples/template-metadata.json, which gives every bundled template a curated title, domain, level, aliases, and scenario tags. Templates marked "primary": true win for canonical family prompts (e.g. ac_RA0029_AgenticAI_root.drawio for "Agentic AI on SAP BTP"). Trust those rankings over raw visible labels such as Page-1.

Selection guidance once you've reviewed candidates:

1. Pick the level first (L0/L1/L2) — levels.md.
2. Pick the closest scenario family: identity → IAS / IAM templates; data flow → Task Center / Build Work Zone; networking → Private Link / OData PrivateLink; AI umbrella → ac_RA0029_AgenticAI_root.drawio; pure A2A/MCP → ac_RA0029_A2A_MCP.drawio; embodied/robotic → ac_RA0029_EmbodiedAIAgents.drawio; multitenancy → SuSaaS.
3. If two templates are close, prefer the simpler one. Don't try to inherit the busiest available diagram.

Known anchor templates:

• Full Agentic AI / AI Agents with Joule landscape → ac_RA0029_AgenticAI_root.drawio. This is the SAP Architecture Center-style template with SAP Joule, SAP BTP subaccount, Network divider, 3rd Party area, SAP Cloud Solutions, SAP Cloud Identity Services, and Architecture Center footer. Use ac_RA0029_EmbodiedAIAgents.drawio only when the prompt explicitly says embodied, robotic, physical agents, or custom implementation layer.
• Focused A2A / MCP flow → ac_RA0029_A2A_MCP.drawio.
• Joule tool ecosystem overview → ac_RA0029_JouleAgentsToolsEcosystem.drawio.

After scaffold has copied a template, preserve the SAP visual frame — title band, zone containers, legend (if any), SAP logos, network divider, Architecture Center footer / QR / reference id (if any), identity flow placement, and the selected template's canvas size. For new diagrams without a clear source template, use 1169 × 827. Rename <diagram name="…"> to your subject. Prefer surgical relabeling over deletion. If cards or edges must change, duplicate existing template cells and keep similar zone density, icon count, pill count, and connector rhythm. The fastest way to a good diagram is renaming labels, swapping icons in-place, and adding a few cards next to the existing ones; the slowest way is rewriting the file.

If the user's scenario is simpler than the chosen template, thin the template deliberately instead of preserving irrelevant branches:

1. Keep the frame, zones, footer, colors, icon scale, and main connector rhythm.
2. Pick the single main flow first; delete only whole unused branches (card + its incoming/outgoing edges + its pills/number markers).
3. Never leave dangling edge references. After each deletion pass, run validate.py; orphaned edges are structural warnings that generated diagrams should fix before delivery.
4. Re-space cards as groups inside their zones; keep sibling cards aligned on common x/y centers and keep at least 40 px between cards and pills.
5. Prefer moving pills into connector gaps over adding edge text. If a pill no longer explains a real edge, delete it with that branch.
6. If thinning removes more than roughly one third of the template, switch to render_semantic.py or pick a simpler SAP reference template.

For Architecture Center templates such as ac_RA0029_AgenticAI_root.drawio, do not replace the white canvas, footer, network divider, or SAP-branded area structure with a dark dashboard layout. If the user asks for a "legend" but the chosen template has no separate bottom legend, satisfy that by preserving the existing inline pills/labels and printing the flow narration after the diagram.

Do not draw from scratch. Starting from a pristine template is the single highest-fidelity trick in this skill. Building a .drawio directly with Write/Edit (without scaffold_diagram.py first) is the most common cause of validator errors, dark backgrounds, novelty pill verbs, and bent edges.

2b. Semantic fallback for ceiling-limited templates

Use this only when scaffold candidates are the wrong architecture family or the user asks for a new composition that cannot be expressed by relabeling one template. The renderer supports a small set of BTP archetypes and produces grid-snapped SAP-style XML with anchored orthogonal edges:

python3 .claude/skills/sap-architecture/scripts/render_semantic.py \
  "<the user's full diagram request>" \
  --out <destination.drawio>

Override the archetype only when the automatic choice is wrong:

python3 .claude/skills/sap-architecture/scripts/render_semantic.py \
  "<request>" --archetype security-operations --out <destination.drawio>

Supported archetypes: security-operations, devops, on-prem-connectivity, private-connectivity, btp-application, data-integration, integration-flow, ai-agent.

Use on-prem-connectivity for SAP Cloud Connector / SAP Connectivity service / SAP Destination service / on-premise SAP S/4HANA flows, including ARC-1 from VS Code through Cloud Foundry. Use btp-application for generic Fiori/App Router/CAP/HANA Cloud application diagrams that are not integration-suite flows. Use data-integration for SAP-to-hyperscaler data movement such as Databricks, Snowflake, lakehouse, Datasphere, or data warehouse prompts. After semantic rendering, run the same autofix / validate / render-review loop. If a proper SAP template exists, prefer the template; semantic fallback is for escaping a bad nearest-template geometry ceiling.

3. Place BTP service icons from the bundled library

For every BTP service in your plan, look up the icon:

python3 .claude/skills/sap-architecture/scripts/extract_icon.py "Destination Service" \
  --x 600 --y 300 --id svc-dest --parent 1

Icon size — critical, this is the #1 visible bug: the SAP corpus uses 32×32 px for the vast majority of icons (224× across the 71 templates), then 48×48 (157×) only for focal anchors next to a zone label. The script's defaults are now --w 32 --h 32. Do not override above 48×48 — anything 64+ overpowers the cards and overlaps text. The validator now flags w>64 or h>64 as a warning.

Icon placement — the second most common bug: never drop an icon on top of a card's text. Two safe patterns:

1. Tucked inside a card — set the icon's parent to the card's id, with small local x / y (e.g. x=8 y=8 w=24 h=24). The icon sits in the card's top-left corner.
2. In a dedicated empty region — a 32×32 icon in a slot near the zone label, with no other vertex within ~40 px.

The validator now flags any icon that overlaps a non-icon vertex by more than 25% of the icon's area.

The script:

• Fuzzy-matches the service name against the 100-icon index (assets/icon-index.json)
• Emits a ready-to-paste <mxCell> with the exact SVG data URI the SAP library ships
• Snaps x/y/w/h to the 10-px grid

To list all available icons: extract_icon.py --list

Common service → canonical library name hints: "Destination Service" → sap-destination-service, "Connectivity Service" → sap-connectivity-service, "XSUAA" / "Authorization & Trust" → sap-authorization-and-trust-management-service, "Cloud Connector" → cloud-connector, "Audit Log" → sap-audit-log-service.

Backend products such as SAP S/4HANA are not BTP service icons. Do not let extract_icon.py "SAP S/4HANA" select SAP S/4HANA for Microsoft Teams; the script now fails closed for that query. Use extract_asset.py "sap-s-4hana" --kind sap-brand-name for a product label or extract_asset.py "on-premise-sap" --kind generic-icon for a generic backend icon.

For non-service SAP starter-kit assets, use extract_asset.py instead. It covers the full indexed library surface: BTP service icons, generic icons, connector presets, area/default shapes, essential shapes, number markers, SAP brand-name text, text elements, and annotation/interface pills.

python3 .claude/skills/sap-architecture/scripts/extract_asset.py --list --kind connector
python3 .claude/skills/sap-architecture/scripts/extract_asset.py "direct one-directional" \
  --kind connector --id flow-auth --x 200 --y 300
python3 .claude/skills/sap-architecture/scripts/extract_asset.py "devices non sap" \
  --kind generic-icon --id ext-devices --x 100 --y 200

Prefer these library assets over hand-authored arrows, number bubbles, interface pills, generic device/user icons, or product-name text. SAP explicitly provides these custom draw.io libraries as the starter kit; matching them is higher fidelity than recreating the shapes by style string.

4. Surgical relabel — preserve the template, change only what differs

You scaffolded from a SAP template in step 2. Now make the minimum edits required for the user's scenario:

• Rename the diagram title and zone labels.
• Swap service-card labels (use exact SAP product names: "SAP S/4HANA Cloud", not "S/4HANA").
• Add or swap icons via extract_icon.py / extract_asset.py.
• Adjust connector source/target if you swapped services.

Prefer the deterministic relabel helper for bulk label edits before hand-editing XML:

python3 .claude/skills/sap-architecture/scripts/relabel.py scaffold.drawio labels.json \
  --out candidate.drawio

Use either a visible-label map ({"Old visible label": "New label"}) or an explicit id map ({"ids": {"cell-id": "New label"}, "labels": {...}}). The helper matches visible labels after stripping HTML wrappers and treating <br> as whitespace, so it is safer than ad-hoc search/replace.

Do NOT touch: canvas size, zone hierarchy (e.g. don't nest Joule inside BTP if the reference puts them side by side), network divider, SAP logos, footer band, identity-flow placement. Those carry the SAP visual identity; preserving them is what keeps the score above 90.

For complex scenarios that require more than label edits, switch into Nudge mode below — it converges via small, scored steps with vision feedback, and is much more reliable than trying to land everything in one pass. The manual draw.io workflow (references/manual-workflow.md) remains the safety net for the last 20% of polish.

4a. Study the SAP design recipe before editing

After scaffold, you will get a 📐 SAP design recipe of <template>.drawio block printed to stdout. Read it. It is a precomputed, structural summary of the SAP template you just copied: how many zones, what colors, icon sizes, pill vocabulary, edge anchor proportions, detected layout patterns. This is what makes it look like a SAP diagram.

The recipe answers questions like:

• How many top-level zones does this template have, and what colors are they? (so you don't add or remove zones blindly)
• What pill vocabulary is canonical here? (e.g. RA0029 templates use TRUST/Authenticate/A2A/MCP/ORD; RA0019 IAM templates add SCIM/SAML2/OIDC/Identity Lifecycle)
• How many of the edges in this template use entryX/exitX anchors? (if the SAP template anchors 43/46 edges and yours anchors 0/11, you've found the bug)
• Which icon sizes does this template use? (don't override extract_icon.py defaults to 80×80 if the SAP recipe says 32×32)

If your scenario isn't a perfect match for any one template — for example you're combining patterns from two SAP architectures — use the find_pattern.py script to discover SAP templates that show similar combinations:

# Free-text query
python3 .claude/skills/sap-architecture/scripts/find_pattern.py "joule purple zone with bottom identity flow"

# By required pill vocabulary
python3 .claude/skills/sap-architecture/scripts/find_pattern.py --pill TRUST --pill A2A --pill MCP

# By structural shape
python3 .claude/skills/sap-architecture/scripts/find_pattern.py --zones 4 --icons-min 8

# By detected pattern tag
python3 .claude/skills/sap-architecture/scripts/find_pattern.py --pattern subaccount-nested-in-btp

# Discover what tags exist
python3 .claude/skills/sap-architecture/scripts/find_pattern.py --list-patterns
python3 .claude/skills/sap-architecture/scripts/find_pattern.py --list-pills

The principle: if SAP has done it (or something similar), copy what they did. The 71-template registry is the ground truth. When you need a feature your scaffolded template doesn't have, find the SAP template that has it and copy the same approach — same icon size, same pill verb, same edge anchor pattern, same color role. Don't improvise.

4b. Nudge mode — iterate with vision + scored feedback (HIGHLY RECOMMENDED)

When you (the LLM) are running inside Cursor or Claude Code with image-reading capability, prefer this loop over trying to one-shot the diagram:

python3 .claude/skills/sap-architecture/scripts/iterate.py <candidate>.drawio
# (use --target <ref>.drawio to lock the comparison target explicitly)

iterate.py renders both the candidate and the SAP target template to PNGs, runs the fingerprint comparison, and prints:

• the score and its delta since the previous run (↑+3.2, ↓-1.5, →+0.0)
• paths to the two PNGs you should read with your vision tool
• the lowest-scoring dimensions, ranked
• a concrete numbered next-edit list — pick ONE per iteration, never multiple

Disciplined loop:

1. First pass: finish the surgical relabel (step 4 above), run autofix + iterate.
2. Visual review: read both PNGs with your vision/read tool. Reason about layout, colors, missing pieces.
3. Pick one suggestion from the printed list — usually #1, since it's the highest-weighted gap.
4. Make the edit with Edit/Write tool calls. Keep it small and scoped.
5. autofix + iterate again. Confirm the score went up. If it dropped, undo (git diff or editor history) and try a different approach.
6. Stop at PASS (score ≥ 90) or when the user says it's good. Never thrash beyond plateau without a fresh nudge.

When the user asks something like "move Joule to the left", "use teal for MCP pills", or "the agents look crowded", treat each nudge as one iteration: read the PNGs, find the relevant cells in the XML, make ONE targeted edit, then re-run iterate.

Full loop documentation, including a nudge-to-edit mapping table and recovery patterns, is in references/nudge-workflow.md.

Reference docs (every value cited back to the SAP guideline):

• references/levels.md — L0 / L1 / L2 audience definitions + canvas conventions
• references/layout.md — canvas skeleton, zones, title band, network bar
• references/palette-and-typography.md — Horizon hex values + Helvetica hierarchy
• references/shapes-and-edges.md — zone / card / pill / edge style strings, semantic line colors
• references/do-and-dont.md — consolidated SAP rules (alternation, color proportion, one-logo, line-style semantics, …)
• references/generation-quality.md — title/scope, relationship-label, abstraction-level, and model-output quality checklist
• references/improvement-options.md — researched ranking of generation/evaluation improvement options

Rules that matter most (the ones every junior attempt gets wrong):

0. Icon size is 32×32, max 48×48. Larger icons (the validator now flags w>64 or h>64) overpower cards and overlap text. The bug looks like "huge cyan SAP icons sitting on top of card titles." Use extract_icon.py defaults; do not override unless the icon is a focal anchor. 0a. Edges must dock with entryX/exitX anchors OR have aligned centers. A naked <mxCell edge="1" source="A" target="B"> draws a straight diagonal line through whatever's in the way. The validator now flags edges that pass through unrelated cards. Two fixes per edge:
   • Add edgeStyle=orthogonalEdgeStyle;exitX=1;exitY=0.5;exitDx=0;exitDy=0;entryX=0;entryY=0.5;entryDx=0;entryDy=0; to dock to the right side of source and left side of target.
   • Or reposition source/target so the straight line has no obstacle.
1. Centers must align for straight edges. For an orthogonalEdgeStyle edge between A and B to render without a kink, either A.centerX == B.centerX or A.centerY == B.centerY. See shapes-and-edges.md.
2. absoluteArcSize=1 next to every arcSize. Without it, 16 is percent and zones get 130-px-radius corners. SAP fixes corner radius at 16 px (areas.md).
3. labelBackgroundColor=default on every edge label. Else text bleeds into the #EBF8FF BTP fill.
4. All x/y/w/h integers, multiples of 10. No 239.9999… garbage. Spacing rule of thumb: ≈ height of SAP logo (foundation.md).
5. Font family: Helvetica for generated content. The live SAP corpus also contains Arial and 72 Brand inside copied rich-text labels; preserve inherited template labels, but emit new labels as Helvetica.
6. Inline top-left zone labels. Never a separate header tab.
7. Pills float on parent="1", not as children of a zone.
8. Connector colors are SAP-mandated: trust = pink (#CC00DC), authentication = green (#188918), authorization = indigo (), firewalls = thick grey ().

5. Validate & autofix — MANDATORY

Before reporting the diagram as done, run:

python3 .claude/skills/sap-architecture/scripts/autofix.py --write my-diagram.drawio
python3 .claude/skills/sap-architecture/scripts/validate.py my-diagram.drawio
python3 .claude/skills/sap-architecture/scripts/score_corpus.py --min-score 90 my-diagram.drawio

For diagrams produced by render_semantic.py, the corpus similarity score is expected to be lower because the diagram is not a near-copy of one template. Gate those with the reference-free SAP-likeness score instead:

python3 .claude/skills/sap-architecture/scripts/score_corpus.py --min-sap-like 90 my-diagram.drawio

Autofix handles the mechanical issues: grid snapping, hex case, missing absoluteArcSize=1, wrong strokeWidth, wrong fontFamily.

Validate catches everything the LLM can't easily self-police:

• XML well-formedness + duplicate ids + missing mxGeometry
• Bent-arrow detection (centers not aligned)
• Label overflow (text wider than its shape)
• Edge labels missing labelBackgroundColor
• Palette deviations
• Sibling overlap (ignores pills / transparent cells / contained children)

Do not skip this step. The validator replaces five rounds of "look at the screenshot and tell me what's wrong". If it reports any error, fix it and re-run. Warnings are acceptable if the user has explicitly asked for something off-convention; otherwise fix them.

score_corpus.py reports two different scores: corpus similarity, which is the right gate for template-derived diagrams, and SAP-likeness, which is the right gate for semantic fallback diagrams. If corpus similarity fails for a template-derived candidate, loop:

1. Run compare.py <chosen-template.drawio> my-diagram.drawio.
2. Restore the template's canvas, zone density, icon count, pill count, palette, and line styles where the diff shows drift.
3. Re-run autofix.py, validate.py, and score_corpus.py --min-score 90.

For extra research runs, clone SAP/btp-solution-diagrams and SAP/architecture-center, then pass those directories to score_corpus.py --references <dir>. This lets you compare against SAP's full live corpus without bundling every upstream file in the plugin.

5b. Visual review — the missing piece for the last 20%

The fingerprint score is necessary but not sufficient. Two diagrams can have identical fingerprints yet look very different. For the last-mile polish, render both candidate and reference to PNG and review them side by side:

python3 .claude/skills/sap-architecture/scripts/render_compare.py \
  assets/reference-examples/<the-template-you-scaffolded-from>.drawio \
  my-diagram.drawio \
  --out-dir .cache/review/my-scenario/ \
  --open

This produces review.html with the reference and candidate side-by-side, the structural score breakdown, and actionable suggestions mapped to the lowest-scoring fingerprint dimensions (e.g. "set the canvas to white", "add SAP edge colors", "swap PROMPT pill for TRUST"). The --open flag launches the page in the default browser.

When the user is uncertain about which template to start from, browse the bundled gallery:

python3 .claude/skills/sap-architecture/scripts/template_browser.py
open .cache/template-browser/index.html

Pre-renders all 71 bundled SAP templates into a thumbnail grid with filter, domain badges, and the scaffold_diagram.py --template <name> invocation for each.

6. Export (if requested) + narrate the flow

If the user asked for a PNG/SVG/PDF, export with the bundled render.py wrapper:

python3 .claude/skills/sap-architecture/scripts/render.py my-diagram.drawio \
  --format png --scale 2 --border 10

The wrapper finds the draw.io desktop binary on macOS, Linux, and WSL2 automatically; set $DRAWIO_CLI to override.

Finally, print the flow narration — a numbered list that spells out what each pill means. SAP Architecture Center puts this in the Markdown page below the embedded image, never inside the canvas. Example:

Flow

1. User signs in to SAP Cloud Identity Services (IAS). (green pill)
2. IAS federates the assertion to XSUAA via SAML / OIDC trust. (magenta TRUST pill)
3. Claude Desktop calls the ARC-1 MCP endpoint with the XSUAA JWT. (teal MCP TOOL CALL pill)
4. ARC-1 resolves the user's destination via BTP Destination Service.
5. Cloud Connector opens an mTLS tunnel to the on-prem SAP ABAP system using Principal Propagation (PP). (green mTLS · PP pill)

Supporting files

sap-architecture/
├── SKILL.md                       (this file)
├── references/
│   ├── levels.md                  — L0 / L1 / L2 audience definitions + canvas
│   ├── palette-and-typography.md  — Horizon hex + Helvetica hierarchy + all SAP rules
│   ├── shapes-and-edges.md        — style strings + center-alignment + line semantics
│   ├── layout.md                  — canvas skeleton + zone-by-zone placement
│   ├── do-and-dont.md             — consolidated SAP rules with verbatim quotes
│   ├── manual-workflow.md         — the realistic scaffold + edit + render-compare loop
│   ├── generation-quality.md      — research-backed output checklist
│   ├── external-test-corpus.md    — optional external SAP corpus for evaluation
│   ├── improvement-options.md     — researched ranking of quality-improvement options
│   └── corpus-findings.md         — 2026 corpus profile from SAP's public repos
├── assets/
│   ├── libraries/
│   │   ├── btp-service-icons-all-size-M.xml  — 100 SAP BTP service icons
│   │   ├── sap-generic-icons-size-M-200302.xml
│   │   ├── connectors.xml / area_shapes.xml / default_shapes.xml
│   │   └── essentials.xml / numbers.xml / sap_brand_names.xml / text_elements.xml / annotations_and_interfaces.xml
│   ├── reference-examples/        — 71 pristine SAP ref-arch templates (Apache-2.0)
│   │                                 11 from SAP/btp-solution-diagrams (prefix btp_)
│   │                                 52 from SAP/architecture-center (prefix ac_)
│   │                                 8 curated external SAP references (prefix ext_)
│   │   └── template-metadata.json  — curated scenario titles, aliases, tags, domains, levels
│   ├── icon-index.json            — slug → library label + ready-to-paste mxCell style
│   ├── asset-index.json           — 448 SAP draw.io assets across 10 libraries
│   └── NOTICE.md                  — Apache-2.0 attribution for SAP assets
└── scripts/
    ├── build_icon_index.py        — regenerate icon-index.json after library refresh
    ├── build_asset_index.py       — regenerate asset-index.json after library refresh
    ├── extract_icon.py            — fuzzy service name → mxCell with grid-snapped geometry
    ├── extract_asset.py           — fuzzy any SAP starter-kit asset → mxCell snippet
    ├── relabel.py                 — deterministic id/visible-label replacement helper
    ├── check_asset_coverage.py    — smoke-check library/index/palette coverage
    ├── scaffold_diagram.py        — copy the closest SAP template to a destination (FIRST STEP)
    ├── render_semantic.py         — deterministic SAP-style fallback for ceiling-limited archetypes
    ├── select_reference.py        — request text → ranked SAP template candidates
    ├── template_browser.py        — pre-render the templates into a thumbnail gallery
    ├── render.py                  — drawio CLI wrapper (export to PNG/SVG/PDF)
    ├── render_compare.py          — render candidate + reference, build side-by-side HTML review
    ├── iterate.py                 — Nudge-mode loop: render+score+structured next-steps for the LLM
    ├── profile_template.py        — extract a deep design profile from one .drawio (or build the registry)
    ├── find_pattern.py            — search the SAP template registry by free text, pills, structural counts, or patterns
    ├── compare.py                 — pairwise fingerprint score against one reference
    ├── score_corpus.py            — candidate → best score across all references
    ├── eval_corpus.py             — opt-in Ollama corpus evaluation loop
    ├── validate.py                — structural + alignment + text-fit + palette checks
    └── autofix.py                 — mechanical fixes (grid, hex case, arcSize, strokeWidth)

Anti-patterns — do NOT

• Don't draw from scratch. Use scaffold_diagram.py first — every other anti-pattern below is a downstream consequence of writing the file by hand instead of starting from a SAP template.
• Don't set a dark, branded, or strongly tinted page background. SAP diagrams use a white/transparent canvas. pageBackgroundColor set to #1A1A1A, #0F2740, etc. is a hard validator error.
• Don't invent flow-pill verbs. Pills carry the canonical SAP vocabulary: TRUST, Authenticate, Authentication, Authorization, A2A, MCP, ORD, HTTPS, OData/REST, REST/Token, SAML2/OIDC, OIDC, SCIM, Identity Lifecycle, Group, Role, Role Collection, Source, Target, Destination. Verbs like PROMPT, ROUTE, CONTEXT, DELEGATE, INVOKE, FETCH, EXECUTE are validator warnings — replace them with the SAP equivalent or drop the pill entirely.
• Don't nest a focus zone inside the BTP zone if the SAP reference puts it beside. Example: in ac_RA0029_AgenticAI_root.drawio, Joule is its own purple top-level zone, sibling to the blue BTP Subaccount, not a child. Get the zone hierarchy right first.
• Don't strip the SAP footer / branding band when relabeling a template. Keep the SAP logos, the zone-band identifiers, and any QR / reference code the SAP file ships with.
• Don't connect cards with custom arrows. Use library arrows; recolour with strokeColor only. Connector colors are SAP-mandated: trust=magenta #CC00DC, auth=green #188918, authorization=indigo #5D36FF, structural=slate #475E75, MCP=teal #07838F. The new edge_palette metric in compare.py penalises wrong colors.

When the description is vague

If the user says "make me a BTP deployment diagram" with nothing else, ask ONE clarifying question:

What's the subject app or flow, including the main BTP services, backend systems, and protocol? e.g. "CAP app with XSUAA + HANA Cloud reading from on-prem ECC over OData via Cloud Connector".

Then proceed. Don't ask more than one question — producing a reasonable default and letting the user iterate beats a long back-and-forth.