sync-architecture-docs

name

sync-architecture-docs

description

Keep this repo's architecture diagrams and prose docs in sync with the code as it evolves. Use this whenever the user asks to update/refresh the architecture diagrams, sync docs with the code, audit docs for staleness, or check that docs/architecture.md still matches the implementation — and proactively after any significant change (a new graph node, tool, Lakebase schema, data-pipeline step, auth change, or frontend swap), since the diagrams and READMEs drift silently. Covers refreshing the four Mermaid diagrams in docs/architecture.md, reconciling the known stale-doc patterns, and verifying with greps + Mermaid validity.

Sync architecture docs

Docs and diagrams drift the moment the code moves and nobody notices until a demo or a new teammate hits a wrong fact. This skill is the maintenance loop that re-aligns the repo's architecture docs with the actual implementation. It is not for first-time authoring — the diagrams and canonical docs already exist; you are keeping them true.

Canonical home for diagrams: docs/architecture.md, under the ## End-to-end architecture heading — four layered Mermaid views. Everything else (READMEs, CLAUDE.md) links to it; don't scatter duplicate diagrams elsewhere.

When this applies

Run the loop after work that changes any of: the LangGraph topology (nodes/edges/parallelism), a gather tool, a Lakebase schema or write-back table, the seed/data pipeline, the auth model (OBO vs app-SP, user_api_scopes), the frontend stack, or the LLM endpoints. Also run it on demand when the user asks to "refresh the diagrams" or "audit the docs."

The loop

1. Explore the changed surfaces

Read the source of truth — never describe from memory, names change. If scope is uncertain, fan out parallel Explore agents over these surfaces:

Surface	Source of truth
Graph topology (nodes, edges, parallelism, interrupt())	agent_server/graph/build_graph.py
Gather tools + what each connects to	agent_server/tools/{operational_tool,genie_tool,knowledge_tool}.py
Schemas, endpoints, LLM routes, env vars	agent_server/config.py
App resources, OBO user_api_scopes, seed job tasks	databricks.yml
Seed/data pipeline (UC → Lakebase / pgvector / VS / Genie)	data/** (esp. operational/03_sync_to_lakebase.py, 05_grant_app_sp.py, knowledge/03_build_vs_index.py)
Frontend stack + API calls	frontend/package.json, frontend/src/**

2. Refresh the four Mermaid diagrams in docs/architecture.md

Re-check every node/table/index/endpoint/scope name against step 1, and update where the code moved. The four views and what each must keep accurate:

1. End-to-end overview — seed job → UC / Lakebase / Genie / VS → LangGraph App → Vite SPA.
2. Data / seed pipeline — the setup_and_seed job's chains with real task + table/index names.
3. Agent runtime graph — real node names; each gather node annotated with backend + auth; interrupt() marked on the HITL node; planner marked sequential if Send fan-out is still P2.
4. Permissions / UC + OBO map — the App-SP grants vs the signed-in-user OBO scopes.

Mermaid hygiene (so it renders on GitHub): use ```mermaid fences and flowchart (not the deprecated graph); avoid the reserved id graph; quote labels containing () : <> or use <br/>; keep subgraphs balanced.

3. Reconcile the known stale-doc patterns

These recur — check each across CLAUDE.md, README.md, agent_server/README.md, data/README.md, and docs/**. Each is "what the docs tend to say" → "what's actually true; verify, don't assume":

• Frontend stack — must read Vite + React + TypeScript (served at /ui), not Next.js. Next.js is only correct when describing the upstream agent-langgraph-advanced template.
• Demo narrative vs seeded data — the canonical seeded hero is Henkel (SUP-001) / SKU-1001 adhesive quality (on-hand 40, open POs ~800, Q4 2026). Pitch narratives (e.g. an IGBT shortage) are illustrative only and must say so, not masquerade as the seeded scenario.
• Placeholder/aspirational text — phrases like "no agent code yet" or "WS1 will bring this in" are stale; the code is implemented.
• Planner shape — sequential today; per-SKU/supplier Send fan-out is P2. Don't claim a shared plans reducer key — it produces a recommendation + per-action PlannedActions.
• Auth split — Knowledge (Vector Search) and Analytics (Genie) run OBO (user token); Operational (Lakebase hybrid SQL) runs as the App service principal.
• Lakebase schemas — three: public (operational synced tables + pgvector quality_incidents), supply_chain_planner_memory (checkpointer + store, SP-owned), supply_chain_planner_app (Meridian write-back, SP-owned).

When you confirm a fact that isn't in this list but keeps drifting, add it here so the next run catches it cheaply.

4. Guardrail — don't touch vendored skills

.claude/skills/ is mostly vendored + SHA-pinned upstream copies (see UPSTREAM.md). Editing a vendored SKILL.md body creates phantom drift and breaks the refresh diff. Fix only repo-authored surfaces: the index in README.md, this skill, and any other skill explicitly marked "repo-authored, not vendored." If a vendored skill states something now-wrong about this repo (e.g. a run command), correct it in the repo-authored index/README, not in the vendored body.

5. Verify

• Stale markers gone — grep the tracked docs (exclude .claude/skills/ vendored bodies): grep -rn "Next.js\|e2e-chatbot\|No agent code yet\|Acme" --include='*.md' . should return only intentional hits (upstream-template descriptions, historical "replaces the old placeholder" notes). Investigate anything else.
• Mermaid valid — GitHub renders ```mermaid natively; locally use the bierner.markdown-mermaid VS Code/Cursor extension, or mmdc (@mermaid-js/mermaid-cli) to render each block and catch syntax errors.
• No broken links — if a doc was moved/deleted, grep for stale relative links to it.

Output discipline

Make small, factual edits — this is reconciliation, not a rewrite. Group the changes into one focused docs commit (e.g. docs: sync architecture diagrams + accuracy cleanup) and summarize per file. Don't commit unless the user asks.