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Skills/neolabhq/context-engineering-kit/query
query logo

query

neolabhq/context-engineering-kit
563 installs1K stars
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Installation

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

Summary

Search the FPF knowledge base and display hypothesis details with assurance information

SKILL.md

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
  1. 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 |

Score

0–100
65/ 100

Grade

C

Popularity17/30

563 installs — growing adoption. Source repo has 1,103 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Query skill score badge previewScore badge

Markdown

[![Query skill](https://www.claudemarket.ai/skills/neolabhq/context-engineering-kit/query/badges/score.svg)](https://www.claudemarket.ai/skills/neolabhq/context-engineering-kit/query)

HTML

<a href="https://www.claudemarket.ai/skills/neolabhq/context-engineering-kit/query"><img src="https://www.claudemarket.ai/skills/neolabhq/context-engineering-kit/query/badges/score.svg" alt="Query skill"/></a>

Query FAQ

How do I install the Query skill?

Run “npx skills add https://github.com/neolabhq/context-engineering-kit --skill query” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Query skill do?

Search the FPF knowledge base and display hypothesis details with assurance information The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Query skill free?

Yes. Query is a free, open-source skill published from neolabhq/context-engineering-kit. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Query work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Query works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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