Agent skill

Extract

by athola in athola/claude-night-market

Builds the gauntlet knowledge base from AST extraction and AI enrichment.

MITAuto-check passedKnowledge Management

Install Extract

skills CLI
$ npx skills add athola/claude-night-market --skill extract -a claude-code

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

GitHub CLI
$ gh skill install athola/claude-night-market extract --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/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/gauntlet/skills/extract .claude/skills/extract && 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
extract
GitHub stars
342
Token cost
~510 tokens
SKILL.md length
222 words
Files
1
Skills in repo
159
Repo updated
First seen
Licence
MIT

At a glance

Builds the gauntlet knowledge base from AST extraction and AI enrichment.

  • Works in 7 steps: Identify target directory: use the… → Run AST extraction: invoke the extractor… → AI enrichment: for each extracted entry,… → …
  • Refreshing codebase knowledge for challenges
  • SKILL.md covers When NOT To Use, Steps, Exit Criteria and Category Priority
  • Calls python3

What it does

Extract is an agent skill from athola/claude-night-market. Builds the gauntlet knowledge base from AST extraction and AI enrichment. Use when initializing or refreshing codebase knowledge for challenges.

Its SKILL.md is about 510 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: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Refreshing codebase knowledge for challenges
  • Tasks that involve Knowledge bases

Example prompts

  • “Use the extract skill to build the gauntlet knowledge base from AST extraction and AI enrichment”
  • “/extract”

Requirements

  • Python 3

Workflow steps

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

  1. Identify target directory: use the current working directory
  2. Run AST extraction: invoke the extractor script
  3. AI enrichment: for each extracted entry, enhance the detail
  4. Cross-reference: link related entries across modules by
  5. Merge with annotations: preserve existing curated entries
  6. Save: write to .gauntlet/knowledge.json
  7. Report: show summary by category, coverage gaps, difficulty

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. 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

    Shell commands in SKILL.md call:

    • python3

    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

Extract loads about 510 tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 222 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~38
When it runs · the whole SKILL.md, loaded when a task matches
~510

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 athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 222 words, ~510 tokens.

Download SKILL.mdSave it as .claude/skills/extract/SKILL.md (or your agent's skills folder).
name
extract
description
Builds the gauntlet knowledge base from AST extraction and AI enrichment. Use when initializing or refreshing codebase knowledge for challenges.
model_hint
standard

Extract Codebase Knowledge

Build or rebuild the .gauntlet/knowledge.json knowledge base.

When NOT To Use

  • Tribal knowledge no parser can see (use gauntlet:curate)
  • Building the code graph (use gauntlet:graph-build)

Steps

  1. Identify target directory: use the current working directory or a user-specified path

  2. Run AST extraction: invoke the extractor script

    bash
    python3 ${CLAUDE_PLUGIN_ROOT}/scripts/extractor.py <target-dir>
  3. AI enrichment: for each extracted entry, enhance the detail field with natural language explanation of business logic, data flow, architectural role, and rationale

  4. Cross-reference: link related entries across modules by matching imports, shared types, and data flow paths

  5. Merge with annotations: preserve existing curated entries in .gauntlet/annotations/

  6. Save: write to .gauntlet/knowledge.json

  7. Report: show summary by category, coverage gaps, difficulty distribution

Exit Criteria

  • .gauntlet/knowledge.json exists and is valid JSON after the skill completes; entries from .gauntlet/annotations/ are merged and not overwritten
  • Report shows entry counts broken down by all 7 categories (business_logic, architecture, data_flow, api_contract, pattern, dependency, error_handling) with coverage gaps identified
  • Each extracted entry has a detail field containing a natural language explanation (not just the raw AST node name)
  • Cross-reference links between related entries are present for modules sharing imports, shared types, or data flow paths

Category Priority

  1. business_logic (weight 7)
  2. architecture (weight 6)
  3. data_flow (weight 5)
  4. api_contract (weight 4)
  5. pattern (weight 3)
  6. dependency (weight 2)
  7. error_handling (weight 1)

© athola, MIT. 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 plugins/gauntlet/skills/extract of athola/claude-night-market.

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

Extract 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.

Extract compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Extract this skillathola/claude-night-market342—~510Automated safety check: PassMIT
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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  • Capture Conversation

    outline/outline

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Questions about Extract

What does Extract do?

Builds the gauntlet knowledge base from AST extraction and AI enrichment. Extract is an agent skill from athola/claude-night-market. Builds the gauntlet knowledge base from AST extraction and AI enrichment.

When should I use Extract?

Extract fits situations like: refreshing codebase knowledge for challenges; tasks that involve Knowledge bases.

How do I install Extract in Claude Code?

Run `npx skills add athola/claude-night-market --skill extract -a claude-code`. Or copy the skill folder (plugins/gauntlet/skills/extract in athola/claude-night-market) into .claude/skills/extract in your project. Claude Code loads it when a task matches its description.

How do I install Extract in Codex?

Run `npx skills add athola/claude-night-market --skill extract -a codex`. Or copy the skill folder (plugins/gauntlet/skills/extract in athola/claude-night-market) into .agents/skills/extract in your project. Codex loads it when a task matches its description.

Can I use Extract 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 athola/claude-night-market --skill extract -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/extract, .gemini/skills/extract, .github/skills/extract and .opencode/skills/extract in your project.

What does Extract need to run?

Going by SKILL.md and its folder, Extract needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Extract 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 Extract 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 Extract use?

Extract is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Extract use?

About 510 tokens (SKILL.md is roughly 2k 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 Extract?

Skills that share tags, products or a category with Extract: 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 Extract?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 342 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on October 6, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.