claude-engineering-plugin/plugins/compound-engineering/skills/ce-compound/SKILL.md

name, description, argument-hint

name	description	argument-hint
ce:compound	Document a recently solved problem to compound your team's knowledge	[optional: brief context about the fix]

/compound

Coordinate multiple subagents working in parallel to document a recently solved problem.

Purpose

Captures problem solutions while context is fresh, creating structured documentation in docs/solutions/ with YAML frontmatter for searchability and future reference. Uses parallel subagents for maximum efficiency.

Why "compound"? Each documented solution compounds your team's knowledge. The first time you solve a problem takes research. Document it, and the next occurrence takes minutes. Knowledge compounds.

Usage

/ce:compound                    # Document the most recent fix
/ce:compound [brief context]    # Provide additional context hint

Execution Strategy

Always run full mode by default. Proceed directly to Phase 1 unless the user explicitly requests compact-safe mode (e.g., /ce:compound --compact or "use compact mode").

Compact-safe mode exists as a lightweight alternative — see the Compact-Safe Mode section below. It's there if the user wants it, not something to push.

---

Full Mode

<critical_requirement> Only ONE file gets written - the final documentation.

Phase 1 subagents return TEXT DATA to the orchestrator. They must NOT use Write, Edit, or create any files. Only the orchestrator (Phase 2) writes the final documentation file. </critical_requirement>

Phase 0.5: Auto Memory Scan

Before launching Phase 1 subagents, check the auto memory directory for notes relevant to the problem being documented.

1. Read MEMORY.md from the auto memory directory (the path is known from the system prompt context)
2. If the directory or MEMORY.md does not exist, is empty, or is unreadable, skip this step and proceed to Phase 1 unchanged
3. Scan the entries for anything related to the problem being documented -- use semantic judgment, not keyword matching
4. If relevant entries are found, prepare a labeled excerpt block:

## Supplementary notes from auto memory
Treat as additional context, not primary evidence. Conversation history
and codebase findings take priority over these notes.

[relevant entries here]

5. Pass this block as additional context to the Context Analyzer and Solution Extractor task prompts in Phase 1. If any memory notes end up in the final documentation (e.g., as part of the investigation steps or root cause analysis), tag them with "(auto memory [claude])" so their origin is clear to future readers.

If no relevant entries are found, proceed to Phase 1 without passing memory context.

Phase 1: Parallel Research

<parallel_tasks>

Launch these subagents IN PARALLEL. Each returns text data to the orchestrator.

1. Context Analyzer

• Extracts conversation history
• Identifies problem type, component, symptoms
• Incorporates auto memory excerpts (if provided by the orchestrator) as supplementary evidence when identifying problem type, component, and symptoms
• Validates against schema
• Returns: YAML frontmatter skeleton

2. Solution Extractor

• Analyzes all investigation steps
• Identifies root cause
• Extracts working solution with code examples
• Incorporates auto memory excerpts (if provided by the orchestrator) as supplementary evidence -- conversation history and the verified fix take priority; if memory notes contradict the conversation, note the contradiction as cautionary context
• Returns: Solution content block

3. Related Docs Finder

• Searches docs/solutions/ for related documentation
• Identifies cross-references and links
• Finds related GitHub issues
• Flags any related learning or pattern docs that may now be stale, contradicted, or overly broad
• Returns: Links, relationships, and any refresh candidates

4. Prevention Strategist

• Develops prevention strategies
• Creates best practices guidance
• Generates test cases if applicable
• Returns: Prevention/testing content

5. Category Classifier

• Determines optimal docs/solutions/ category
• Validates category against schema
• Suggests filename based on slug
• Returns: Final path and filename

</parallel_tasks>

Phase 2: Assembly & Write

<sequential_tasks>

WAIT for all Phase 1 subagents to complete before proceeding.

The orchestrating agent (main conversation) performs these steps:

1. Collect all text results from Phase 1 subagents
2. Assemble complete markdown file from the collected pieces
3. Validate YAML frontmatter against schema
4. Create directory if needed: mkdir -p docs/solutions/[category]/
5. Write the SINGLE final file: docs/solutions/[category]/[filename].md

</sequential_tasks>

Phase 2.5: Selective Refresh Check

After writing the new learning, decide whether this new solution is evidence that older docs should be refreshed.

ce:compound-refresh is not a default follow-up. Use it selectively when the new learning suggests an older learning or pattern doc may now be inaccurate.

It makes sense to invoke ce:compound-refresh when one or more of these are true:

1. A related learning or pattern doc recommends an approach that the new fix now contradicts
2. The new fix clearly supersedes an older documented solution
3. The current work involved a refactor, migration, rename, or dependency upgrade that likely invalidated references in older docs
4. A pattern doc now looks overly broad, outdated, or no longer supported by the refreshed reality
5. The Related Docs Finder surfaced high-confidence refresh candidates in the same problem space

It does not make sense to invoke ce:compound-refresh when:

1. No related docs were found
2. Related docs still appear consistent with the new learning
3. The overlap is superficial and does not change prior guidance
4. Refresh would require a broad historical review with weak evidence

Use these rules:

• If there is one obvious stale candidate, invoke ce:compound-refresh with a narrow scope hint after the new learning is written
• If there are multiple candidates in the same area, ask the user whether to run a targeted refresh for that module, category, or pattern set
• If context is already tight or you are in compact-safe mode, do not expand into a broad refresh automatically; instead recommend ce:compound-refresh as the next step with a scope hint

When invoking or recommending ce:compound-refresh, be explicit about the argument to pass. Prefer the narrowest useful scope:

• Specific file when one learning or pattern doc is the likely stale artifact
• Module or component name when several related docs may need review
• Category name when the drift is concentrated in one solutions area
• Pattern filename or pattern topic when the stale guidance lives in docs/solutions/patterns/

Examples:

• /ce:compound-refresh plugin-versioning-requirements
• /ce:compound-refresh payments
• /ce:compound-refresh performance-issues
• /ce:compound-refresh critical-patterns

A single scope hint may still expand to multiple related docs when the change is cross-cutting within one domain, category, or pattern area.

Do not invoke ce:compound-refresh without an argument unless the user explicitly wants a broad sweep.

Always capture the new learning first. Refresh is a targeted maintenance follow-up, not a prerequisite for documentation.

Phase 3: Optional Enhancement

WAIT for Phase 2 to complete before proceeding.

<parallel_tasks>

Based on problem type, optionally invoke specialized agents to review the documentation:

• performance_issue → performance-oracle
• security_issue → security-sentinel
• database_issue → data-integrity-guardian
• test_failure → cora-test-reviewer
• Any code-heavy issue → kieran-rails-reviewer + code-simplicity-reviewer

</parallel_tasks>

---

Compact-Safe Mode

<critical_requirement> Single-pass alternative for context-constrained sessions.

When context budget is tight, this mode skips parallel subagents entirely. The orchestrator performs all work in a single pass, producing a minimal but complete solution document. </critical_requirement>

The orchestrator (main conversation) performs ALL of the following in one sequential pass:

1. Extract from conversation: Identify the problem, root cause, and solution from conversation history. Also read MEMORY.md from the auto memory directory if it exists -- use any relevant notes as supplementary context alongside conversation history. Tag any memory-sourced content incorporated into the final doc with "(auto memory [claude])"
2. Classify: Determine category and filename (same categories as full mode)
3. Write minimal doc: Create docs/solutions/[category]/[filename].md with:
   • YAML frontmatter (title, category, date, tags)
   • Problem description (1-2 sentences)
   • Root cause (1-2 sentences)
   • Solution with key code snippets
   • One prevention tip
4. Skip specialized agent reviews (Phase 3) to conserve context

Compact-safe output:

✓ Documentation complete (compact-safe mode)

File created:
- docs/solutions/[category]/[filename].md

Note: This was created in compact-safe mode. For richer documentation
(cross-references, detailed prevention strategies, specialized reviews),
re-run /compound in a fresh session.

No subagents are launched. No parallel tasks. One file written.

In compact-safe mode, only suggest ce:compound-refresh if there is an obvious narrow refresh target. Do not broaden into a large refresh sweep from a compact-safe session.

---

What It Captures

• Problem symptom: Exact error messages, observable behavior
• Investigation steps tried: What didn't work and why
• Root cause analysis: Technical explanation
• Working solution: Step-by-step fix with code examples
• Prevention strategies: How to avoid in future
• Cross-references: Links to related issues and docs

Preconditions

Problem has been solved (not in-progress) Solution has been verified working Non-trivial problem (not simple typo or obvious error)

What It Creates

Organized documentation:

• File: docs/solutions/[category]/[filename].md

Categories auto-detected from problem:

• build-errors/
• test-failures/
• runtime-errors/
• performance-issues/
• database-issues/
• security-issues/
• ui-bugs/
• integration-issues/
• logic-errors/

Common Mistakes to Avoid

❌ Wrong	✅ Correct
Subagents write files like context-analysis.md, solution-draft.md	Subagents return text data; orchestrator writes one final file
Research and assembly run in parallel	Research completes → then assembly runs
Multiple files created during workflow	Single file: docs/solutions/[category]/[filename].md

Success Output

✓ Documentation complete

Auto memory: 2 relevant entries used as supplementary evidence

Subagent Results:
  ✓ Context Analyzer: Identified performance_issue in brief_system
  ✓ Solution Extractor: 3 code fixes
  ✓ Related Docs Finder: 2 related issues
  ✓ Prevention Strategist: Prevention strategies, test suggestions
  ✓ Category Classifier: `performance-issues`

Specialized Agent Reviews (Auto-Triggered):
  ✓ performance-oracle: Validated query optimization approach
  ✓ kieran-rails-reviewer: Code examples meet Rails standards
  ✓ code-simplicity-reviewer: Solution is appropriately minimal
  ✓ every-style-editor: Documentation style verified

File created:
- docs/solutions/performance-issues/n-plus-one-brief-generation.md

This documentation will be searchable for future reference when similar
issues occur in the Email Processing or Brief System modules.

What's next?
1. Continue workflow (recommended)
2. Link related documentation
3. Update other references
4. View documentation
5. Other

The Compounding Philosophy

This creates a compounding knowledge system:

1. First time you solve "N+1 query in brief generation" → Research (30 min)
2. Document the solution → docs/solutions/performance-issues/n-plus-one-briefs.md (5 min)
3. Next time similar issue occurs → Quick lookup (2 min)
4. Knowledge compounds → Team gets smarter

The feedback loop:

Build → Test → Find Issue → Research → Improve → Document → Validate → Deploy
    ↑                                                                      ↓
    └──────────────────────────────────────────────────────────────────────┘

Each unit of engineering work should make subsequent units of work easier—not harder.

Auto-Invoke

<auto_invoke> <trigger_phrases> - "that worked" - "it's fixed" - "working now" - "problem solved" </trigger_phrases>

<manual_override> Use /ce:compound [context] to document immediately without waiting for auto-detection. </manual_override> </auto_invoke>

Routes To

compound-docs skill

Applicable Specialized Agents

Based on problem type, these agents can enhance documentation:

Code Quality & Review

• kieran-rails-reviewer: Reviews code examples for Rails best practices
• code-simplicity-reviewer: Ensures solution code is minimal and clear
• pattern-recognition-specialist: Identifies anti-patterns or repeating issues

Specific Domain Experts

• performance-oracle: Analyzes performance_issue category solutions
• security-sentinel: Reviews security_issue solutions for vulnerabilities
• cora-test-reviewer: Creates test cases for prevention strategies
• data-integrity-guardian: Reviews database_issue migrations and queries

Enhancement & Documentation

• best-practices-researcher: Enriches solution with industry best practices
• every-style-editor: Reviews documentation style and clarity
• framework-docs-researcher: Links to Rails/gem documentation references

When to Invoke

• Auto-triggered (optional): Agents can run post-documentation for enhancement
• Manual trigger: User can invoke agents after /ce:compound completes for deeper review
• Customize agents: Edit compound-engineering.local.md or invoke the setup skill to configure which review agents are used across all workflows

Related Commands

• /research [topic] - Deep investigation (searches docs/solutions/ for patterns)
• /ce:plan - Planning workflow (references documented solutions)