/query
Search the FPF knowledge base and display hypothesis details with assurance information
$ npx -y skills add NeoLabHQ/context-engineering-kit --skill query --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/query
Context preview
The summary Claude sees to decide when to auto-load this skill.
Search the FPF knowledge base and display hypothesis details with assurance information
SKILL.md
query.SKILL.mdname: query
description: "Search the FPF knowledge base and display hypothesis details with assurance information"
Query Knowledge
Search the FPF knowledge base and display hypothesis details with assurance information.
Action (Run-Time)
1. **Search** `.fpf/knowledge/` and `.fpf/decisions/` by user query. 2. **For each found hypothesis**, display:
- Basic info: title, layer (L0/L1/L2), kind, scope
- If layer >= L1: read audit section for R_eff
- If has dependencies: show dependency graph
- Evidence summary if exists
3. **Present results** in table format.
Search Locations
| 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 |
Output Format
## 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 Methods
By Keyword
Search file contents for matching text:
/fpf:query caching
-> Finds all hypotheses with "caching" in title or content
By Specific ID
Look up a specific hypothesis:
/fpf:query redis-caching
-> Shows full details for redis-caching
-> Displays dependency tree
-> Shows R_eff breakdown
By Layer
Filter by knowledge layer:
/fpf:query L2
-> Lists all L2 hypotheses with R_eff scores
By Decision
Search decision records:
/fpf:query DRR
-> Lists all Design Rationale Records
-> Shows what each DRR selected/rejected
R_eff Display
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
Dependency Tree Display
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 score
- `CL:N` = Congruence Level (1-3)
Examples
**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 |
Read more
name: query description: "Search the FPF knowledge base and display hypothesis details with assurance information"
Query Knowledge
Search the FPF knowledge base and display hypothesis details with assurance information.
Action (Run-Time)
1. **Search** `.fpf/knowledge/` and `.fpf/decisions/` by user query. 2. **For each found hypothesis**, display:
- Basic info: title, layer (L0/L1/L2), kind, scope
- If layer >= L1: read audit section for R_eff
- If has dependencies: show dependency graph
- Evidence summary if exists
3. **Present results** in table format.
Search Locations
| 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 |
Output Format
## 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 Methods
By Keyword
Search file contents for matching text:
/fpf:query caching -> Finds all hypotheses with "caching" in title or content
By Specific ID
Look up a specific hypothesis:
/fpf:query redis-caching -> Shows full details for redis-caching -> Displays dependency tree -> Shows R_eff breakdown
By Layer
Filter by knowledge layer:
/fpf:query L2 -> Lists all L2 hypotheses with R_eff scores
By Decision
Search decision records:
/fpf:query DRR -> Lists all Design Rationale Records -> Shows what each DRR selected/rejected
R_eff Display
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
Dependency Tree Display
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 score
- `CL:N` = Congruence Level (1-3)
Examples
**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 |
A hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint, focused on improving agent result quality and predictability.
Repo: NeoLabHQ/context-engineering-kit
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Open skill

