Reconcile the project's FPF state with recent repository changes
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Search the FPF knowledge base and display hypothesis details with assurance information
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Search the FPF knowledge base and display hypothesis details with assurance information.
.fpf/knowledge/ and .fpf/decisions/ by user query.| Location | Contents |
|---|---|
.fpf/knowledge/L0/ | Proposed hypotheses |
.fpf/knowledge/L1/ | Verified hypotheses |
.fpf/knowledge/L2/ | Validated hypotheses |
.fpf/knowledge/invalid/ | Rejected hypotheses |
.fpf/decisions/ | Design Rationale Records |
.fpf/evidence/ | Evidence and audit files |
## Search Results for "<query>"
### Hypotheses Found
| Hypothesis | Layer | Kind | R_eff |
|------------|-------|------|-------|
| redis-caching | L2 | system | 0.85 |
| cdn-edge | L2 | system | 0.72 |
### redis-caching (L2)
**Title**: Use Redis for Caching
**Kind**: system
**Scope**: High-load systems, Linux only
**R_eff**: 0.85
**Weakest Link**: internal test (0.85)
**Dependencies**:
[redis-caching R:0.85] └── (no dependencies)
**Evidence**:
- ev-benchmark-redis-caching-2025-01-15 (internal, PASS)
### cdn-edge (L2)
**Title**: Use CDN Edge Cache
**Kind**: system
**Scope**: Static content delivery
**R_eff**: 0.72
**Weakest Link**: external docs (CL1 penalty)
**Evidence**:
- ev-research-cdn-2025-01-10 (external, PASS)
Search file contents for matching text:
/fpf:query caching
-> Finds all hypotheses with "caching" in title or content
Look up a specific hypothesis:
/fpf:query redis-caching
-> Shows full details for redis-caching
-> Displays dependency tree
-> Shows R_eff breakdown
Filter by knowledge layer:
/fpf:query L2
-> Lists all L2 hypotheses with R_eff scores
Search decision records:
/fpf:query DRR
-> Lists all Design Rationale Records
-> Shows what each DRR selected/rejected
For L1+ hypotheses, read the audit section and display:
**R_eff Breakdown**:
- Self Score: 1.00
- Weakest Link: ev-research-redis (0.90)
- Dependency Penalty: none
- **Final R_eff**: 0.85
If hypothesis has depends_on, show the tree:
[api-gateway R:0.80]
└──(CL:3)── [auth-module R:0.85]
└──(CL:2)── [rate-limiter R:0.90]
Legend:
R:X.XX = R_eff scoreCL:N = Congruence Level (1-3)Search by keyword:
User: /fpf:query caching
Results:
| Hypothesis | Layer | R_eff |
|------------|-------|-------|
| redis-caching | L2 | 0.85 |
| cdn-edge-cache | L2 | 0.72 |
| lru-cache | invalid | N/A |
Query specific hypothesis:
User: /fpf:query redis-caching
# redis-caching (L2)
Title: Use Redis for Caching
Kind: system
Scope: High-load systems
R_eff: 0.85
Evidence: 2 files
Query decisions:
User: /fpf:query DRR
# Design Rationale Records
| DRR | Date | Winner | Rejected |
|-----|------|--------|----------|
| DRR-2025-01-15-caching | 2025-01-15 | redis-caching | cdn-edge |
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Reconcile the project's FPF state with recent repository changes
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
creates draft task file in .specs/tasks/draft/ with original user intent
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Evaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.
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Auto-selects best Kaizen method (Gemba Walk, Value Stream, or Muda) for target
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Comprehensive A3 one-page problem analysis with root cause and action plan
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Analyze a GitHub issue and create a detailed technical specification
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