vonbai/cotx-engine/cotx-scan

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Architecture scanning skill. Reviews auto-generated architecture and enriches with domain-specific descriptions, diagram adjustments, and boundary corrections. Use when the user says "cotx scan", "scan architecture", "enrich architecture", or "update architecture perspectives".

Install

npx vskill@latest install vonbai/cotx-engine/cotx-scan

SKILL.md

cotx-scan — Evidence-Backed Architecture Scanner

Purpose

Review and enrich cotx architecture context using the canonical workspace and graph-backed evidence.

The agent should not start by Glob/Read over the full source tree. cotx's static analysis and workspace scan provide bounded starting context. Use MCP tools first, then read targeted source files only when needed to verify implementation details, resolve graph gaps, or answer a question that the map cannot support.

  • .cotx/workspace-layout.json is a deterministic layout sidecar, not truth graph.
  • .cotx/architecture/workspace.json is the canonical C4/Structurizr-style architecture model.
  • .cotx/architecture/recursion-plan.json records deterministic leaf/recurse decisions.
  • LLM or agent output may enrich narrative fields only. It must not create graph truth.

Step 1: Get Minimal Context

cotx_minimal_context project_root=<project_root> task="scan architecture" budget=standard

If .cotx/ is missing, run cotx_compile first. Do not read the full repository.


Step 2: Review Architecture Summary

cotx_map scope=architecture

This includes the workspace layout summary and available architecture perspectives. The canonical workspace is the source for future exports; legacy perspective sidecars remain readable context.


Step 3: Read Targeted Context

Use targeted cotx tools:

cotx_map scope=overview
cotx_context node_id=architecture/<perspective-id>
cotx_context node_id=architecture/<perspective-id>/<component-id>
cotx_query query="<domain term>" layer=architecture

Step 4: Enrich Only With Evidence

For each enrichment draft:

  • Cite evidence anchors from returned cotx context.
  • Use cotx_write only for enrichment or architecture narrative fields.
  • Do not mutate deterministic files, functions, edges, routes, tools, processes, or workspace facts.
  • Prefer writing descriptions over diagrams. Adjust diagrams only when the rendered view is misleading and IDs still map to canonical elements.
cotx_write node_id=architecture/<perspective-id> field=description content="..."
cotx_write node_id=architecture/<perspective-id>/<component-id> field=description content="..."

Step 5: Recursive Drill-Down

Use the recursion plan when available. Recurse only into elements marked recurse; treat leaf as terminal unless new graph evidence contradicts it.


Step 6: Verify

Search for key domain concepts to confirm the architecture is queryable:

cotx_query query="<key domain term>" layer=architecture

Verify that results point to relevant perspectives and components.


Tips

  • Descriptions answer "why": Write what responsibility a component owns, not what files it contains. The data already shows files.
  • Don't over-recurse: If a component has 2-3 files and one purpose, it's a leaf. Recurse only when there are genuinely distinct sub-responsibilities.
  • For monorepos: Check workspace layout and package boundaries before module-level interpretation.
  • Preserve deterministic data: Auto-generated workspace/graph data captures structural truth; agent descriptions add semantic meaning.

Important

  • Do NOT start with broad source reads. Use cotx tools first, then read targeted files when the graph/context is insufficient or needs verification.
  • Do NOT modify files, exported_functions, or other structural fields — only description and diagram.
  • Do NOT create or mutate truth graph facts from LLM output.
  • Write each field as a separate cotx_write call.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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