SuperClaude/docs/Development/pm-agent-improvements.md
Mithun Gowda B faa53f27da
Revert "feat: comprehensive framework improvements (#447)" (#453)
This reverts commit 00706f0ea99aa04f54a3ddf5244738b0a9b37a91.
2025-10-21 09:48:41 +05:30

5.6 KiB

PM Agent Improvement Implementation - 2025-10-14

Implemented Improvements

1. Self-Correcting Execution (Root Cause First)

Core Change: Never retry the same approach without understanding WHY it failed.

Implementation:

  • 6-step error detection protocol
  • Mandatory root cause investigation (context7, WebFetch, Grep, Read)
  • Hypothesis formation before solution attempt
  • Solution must be DIFFERENT from previous attempts
  • Learning capture for future reference

Anti-Patterns Explicitly Forbidden:

  • "エラーが出た。もう一回やってみよう"
  • Retry 1, 2, 3 times with same approach
  • "Warningあるけど動くからOK"

Correct Patterns Enforced:

  • Error → Investigate official docs
  • Understand root cause → Design different solution
  • Document learning → Prevent future recurrence

2. Warning/Error Investigation Culture

Core Principle: 全ての警告・エラーに興味を持って調査する

Implementation:

  • Zero tolerance for dismissal
  • Mandatory investigation protocol (context7 + WebFetch)
  • Impact categorization (Critical/Important/Informational)
  • Documentation requirement for all decisions

Quality Mindset:

  • Warnings = Future technical debt
  • "Works now" ≠ "Production ready"
  • Thorough investigation = Higher code quality
  • Every warning is a learning opportunity

3. Memory Key Schema (Standardized)

Pattern: [category]/[subcategory]/[identifier]

Inspiration: Kubernetes namespaces, Git refs, Prometheus metrics

Categories Defined:

  • session/: Session lifecycle management
  • plan/: Planning phase (hypothesis, architecture, rationale)
  • execution/: Do phase (experiments, errors, solutions)
  • evaluation/: Check phase (analysis, metrics, lessons)
  • learning/: Knowledge capture (patterns, solutions, mistakes)
  • project/: Project understanding (context, architecture, conventions)

Benefits:

  • Consistent naming across all memory operations
  • Easy to query and retrieve related memories
  • Clear organization for knowledge management
  • Inspired by proven OSS practices

4. PDCA Document Structure (Normalized)

Location: docs/pdca/[feature-name]/

Structure (明確・わかりやすい):

docs/pdca/[feature-name]/
  ├── plan.md    # Plan: 仮説・設計
  ├── do.md      # Do: 実験・試行錯誤  
  ├── check.md   # Check: 評価・分析
  └── act.md     # Act: 改善・次アクション

Templates Provided:

  • plan.md: Hypothesis, Expected Outcomes, Risks
  • do.md: Implementation log (時系列), Learnings
  • check.md: Results vs Expectations, What worked/failed
  • act.md: Success patterns, Global rule updates, Checklist updates

Lifecycle:

  1. Start → Create plan.md
  2. Work → Update do.md continuously
  3. Complete → Create check.md
  4. Success → Formalize to docs/patterns/ + create act.md
  5. Failure → Move to docs/mistakes/ + create act.md with prevention

User Feedback Integration

Key Insights from User:

  1. 同じ方法を繰り返すからループする → Root cause analysis mandatory
  2. 警告を興味を持って調べる癖 → Zero tolerance culture implemented
  3. スキーマ未定義なら定義すべき → Kubernetes-inspired schema added
  4. plan/do/check/actでわかりやすい → PDCA structure normalized
  5. OSS参考にアイデアをパクる → Kubernetes, Git, Prometheus patterns adopted

Philosophy Embedded:

  • "間違いを理解してから再試行" (Understand before retry)
  • "警告 = 将来の技術的負債" (Warnings = Future debt)
  • "コード品質向上 = 徹底調査文化" (Quality = Investigation culture)
  • "アイデアに著作権なし" (Ideas are free to adopt)

Expected Impact

Code Quality:

  • Fewer repeated errors (root cause analysis)
  • Proactive technical debt prevention (warning investigation)
  • Higher test coverage and security compliance
  • Consistent documentation and knowledge capture

Developer Experience:

  • Clear PDCA structure (plan/do/check/act)
  • Standardized memory keys (easy to use)
  • Learning captured systematically
  • Patterns reusable across projects

Long-term Benefits:

  • Continuous improvement culture
  • Knowledge accumulation over sessions
  • Reduced time on repeated mistakes
  • Higher quality autonomous execution

Next Steps

  1. Test in Real Usage: Apply PM Agent to actual feature implementation
  2. Validate Improvements: Measure error recovery cycles, warning handling
  3. Iterate Based on Results: Refine based on real-world performance
  4. Document Success Cases: Build example library of PDCA cycles
  5. Upstream Contribution: After validation, contribute to SuperClaude

Files Modified

  • superclaude/commands/pm.md:
    • Added "Self-Correcting Execution (Root Cause First)" section
    • Added "Warning/Error Investigation Culture" section
    • Added "Memory Key Schema (Standardized)" section
    • Added "PDCA Document Structure (Normalized)" section
    • ~260 lines of detailed implementation guidance

Implementation Quality

  • User feedback directly incorporated
  • Real-world practices from Kubernetes, Git, Prometheus
  • Clear anti-patterns and correct patterns defined
  • Concrete examples and templates provided
  • Japanese and English mixed (user preference respected)
  • Philosophical principles embedded in implementation

This improvement represents a fundamental shift from "retry on error" to "understand then solve" approach, which should dramatically improve PM Agent's code quality and learning capabilities.