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

GPL-3.0Auto-check passedKnowledge Management

Install Query

skills CLI
$ npx skills add NeoLabHQ/context-engineering-kit --skill query -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NeoLabHQ/context-engineering-kit query --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/query .claude/skills/query && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
query
GitHub stars
1.7k
Token cost
~861 tokens
SKILL.md length
159 words
Files
1
Skills in repo
57
Repo updated
First seen
Licence
GPL-3.0

At a glance

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

  • Works in 3 steps: Search .fpf/knowledge/ and… → For each found hypothesis, display → Present results in table format.
  • Tasks that involve Knowledge bases
  • SKILL.md covers Action (Run-Time), Search Locations, Output Format and Search Methods, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Query is an agent skill from NeoLabHQ/context-engineering-kit. Search the FPF knowledge base and display hypothesis details with assurance information

Its SKILL.md is about 860 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Knowledge bases. The repository describes itself as: Hand-crafted Claude Code Skills focused on improving agent results quality. Compatible with OpenCode, Cursor, Antigravity, Gemini CLI, and others. Includes CodeRabbit open-source… The licence is GPL-3.0.

When your agent uses it

  • Tasks that involve Knowledge bases

Example prompts

  • “/query”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Search .fpf/knowledge/ and .fpf/decisions/ by user query.
  2. For each found hypothesis, display
  3. Present results in table format.

What it can do on your machine

Read from SKILL.md and the folder at commit 23e2428. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Query loads about 861 tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 159 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~861

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NeoLabHQ/context-engineering-kit at commit 23e2428, republished under its GPL-3.0 licence (© NeoLabHQ). 159 words, ~861 tokens.

Download SKILL.mdSave it as .claude/skills/query/SKILL.md (or your agent's skills folder).
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

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

markdown
## 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:

markdown
**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 |

© NeoLabHQ, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/query of NeoLabHQ/context-engineering-kit.

Open the folder on GitHubat commit 23e2428

Compare with similar skills

Query next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Query compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Query this skillNeoLabHQ/context-engineering-kit1.7k—~861Automated safety check: PassGPL-3.0
Capture Conversationoutline/outline41k—~474Automated safety check: PassCustom licence
Project CairniBlinkQ/project-cairn2352 repos~861Automated safety check: PassMIT
LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything86k1 repos~1.5kAutomated safety check: PassMIT
Find And Citeoutline/outline41k—~537Automated safety check: PassCustom licence
Xhs Virtual Productchenjin-cmd/xhs-virtual-product727—~862Automated safety check: PassMIT

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Questions about Query

What does Query do?

Search the FPF knowledge base and display hypothesis details with assurance information. Query is an agent skill from NeoLabHQ/context-engineering-kit.

When should I use Query?

Query fits situations like: tasks that involve Knowledge bases.

How do I install Query in Claude Code?

Run `npx skills add NeoLabHQ/context-engineering-kit --skill query -a claude-code`. Or copy the skill folder (skills/query in NeoLabHQ/context-engineering-kit) into .claude/skills/query in your project. Claude Code loads it when a task matches its description.

How do I install Query in Codex?

Run `npx skills add NeoLabHQ/context-engineering-kit --skill query -a codex`. Or copy the skill folder (skills/query in NeoLabHQ/context-engineering-kit) into .agents/skills/query in your project. Codex loads it when a task matches its description.

Can I use Query in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NeoLabHQ/context-engineering-kit --skill query -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/query, .gemini/skills/query, .github/skills/query and .opencode/skills/query in your project.

What does Query need to run?

SKILL.md names no scripts, command-line tools or credentials: Query is instructions for the agent only.

Does Query access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Query safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Query use?

Query is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Query use?

About 861 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Query?

Skills that share tags, products or a category with Query: Capture Conversation (outline/outline, 41k stars), Project Cairn (iBlinkQ/project-cairn, 235 stars), LLM Wiki Knowledge Graph (Egonex-AI/Understand-Anything, 86k stars) and Find And Cite (outline/outline, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Query?

NeoLabHQ (a GitHub organization) maintains it in NeoLabHQ/context-engineering-kit, which has 1,748 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on August 26, 2026.

Source: NeoLabHQ/context-engineering-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.