workflows-compound

Arguments

[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

/workflows-compound                    # Document the most recent fix
/workflows-compound [brief context]    # Provide additional context hint

Execution Strategy: Two-Phase Orchestration

<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 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
• Validates against schema
• Returns: YAML frontmatter skeleton

2. Solution Extractor

• Analyzes all investigation steps
• Identifies root cause
• Extracts working solution with code examples
• Returns: Solution content block

3. Related Docs Finder

• Searches docs/solutions/ for related documentation
• Identifies cross-references and links
• Finds related GitHub issues
• Returns: Links and relationships

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

6. Execution Session Analyzer

• Searches docs/execution-sessions/ for recent session files related to the current fix
• Reads session files and extracts recurring patterns (e.g., same error across multiple tasks)
• Identifies problems that were encountered and how they were fixed during execution
• Cross-references with the current problem being documented
• Returns: Execution context and recurring patterns

</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 Include execution session learnings: If the Execution Session Analyzer found relevant session files, incorporate execution learnings into the documentation:
   • Add an "## Execution Context" section if problems were first discovered during task execution
   • Include the progression of how the problem was encountered and resolved across multiple task attempts
   • Reference the session file path for traceability (e.g., docs/execution-sessions/work-2026-02-19-143022/task-03-create-auth-service.md)
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 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 → rabak-laravel-reviewer + code-simplicity-reviewer
• Any code-heavy issue → rabak-laravel-reviewer + code-simplicity-reviewer

</parallel_tasks>

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
• Execution session learnings: Patterns and fixes discovered during /workflows-work task execution (from docs/execution-sessions/)

Preconditions

<preconditions enforcement="advisory"> <check condition="problem_solved"> Problem has been solved (not in-progress) </check> <check condition="solution_verified"> Solution has been verified working </check> <check condition="non_trivial"> Non-trivial problem (not simple typo or obvious error) </check> </preconditions>

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

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`
  ✓ Execution Session Analyzer: Found 2 related session files, 1 recurring pattern

Specialized Agent Reviews (Auto-Triggered):
  ✓ performance-oracle: Validated query optimization approach
  ✓ rabak-laravel-reviewer: Code examples meet project standards
  ✓ code-simplicity-reviewer: Solution is appropriately minimal
  ✓ code-simplicity-reviewer: Solution is appropriately minimal

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 → Execute (session files) → 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 /workflows-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

• rabak-laravel-reviewer: Reviews code examples for Laravel 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
• rabak-laravel-reviewer: Reviews code examples for prevention test strategies
• data-integrity-guardian: Reviews database_issue migrations and queries

Enhancement & Documentation

• best-practices-researcher: Enriches solution with industry best practices
• rabak-vue-reviewer: Reviews frontend code for Vue.js conventions
• framework-docs-researcher: Links to Laravel/package documentation references

When to Invoke

• Auto-triggered (optional): Agents can run post-documentation for enhancement
• Manual trigger: User can invoke agents after /workflows-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)
• /workflows-plan - Planning workflow (references documented solutions)