mcpField
Q
query

query

github.com/neolabhqProductivity1.8k1.2k installsUpdated 9w ago
Repository

About query

query is a skill for searching the FPF knowledge base and decision records. It helps users find hypotheses and inspect their assurance information, including effective scores, dependencies, and evidence summaries.

Key features

  1. 01Search knowledge and decision records
  2. 02Filter by keyword, ID, or layer
  3. 03Show hypothesis layers and R_eff scores
  4. 04Display dependency trees and evidence summaries

Use cases

  1. 01Find hypotheses related to caching
  2. 02Inspect a hypothesis's dependencies and score
  3. 03Retrieve design rationale records and selections

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/neolabhq/context-engineering-kit --skill query

After installing, type/queryin Claude Code to confirm it loaded.

Details

From the project README

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

LocationContents
.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 |

Comments

Markdown supported