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Code Foundation Stinger

Organization
legioncodeinc
code-foundation-stinger

Read-only repo health audit: Wasp Nest setup, agent readiness, CI, tests, lint, lockfiles, secrets, governance. Writes contract-shaped foundation findings and measures. Never edits the repo.

Overview

Publisherlegioncodeinc
Repositoryvibe-coding-tools
Skill namecode-foundation-stinger
Stars
94
Forks
44
Bundled files
20
LicenseAGPL-3.0-or-later
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 20 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by legioncodeinc on GitHub. Read the source before you install it.

Installation

Install the Code Foundation Stinger AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/legioncodeinc/vibe-coding-tools/tree/main/plugins/code-audit-tools/skills/code-foundation-stinger
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/legioncodeinc/vibe-coding-tools.git /tmp/vibe-coding-tools
mkdir -p .claude/skills
cp -r /tmp/vibe-coding-tools/plugins/code-audit-tools/skills/code-foundation-stinger .claude/skills/code-foundation-stinger
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Foundation Stinger in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Foundation Stinger on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Foundation Stinger is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Foundation Stinger

Purpose

Answer one question for the /audit-my-code run: is this repository set up so humans and AI agents can work in it safely? This is the Foundation dimension every audit tier runs first. It measures the repository against the baseline that get-started-stinger establishes (Library Schema v2 tree, wasp-nest.lock, CI, dependency automation, CODEOWNERS, README and policy files, .gitignore and .env.example) and extends it with current repository health practice: OpenSSF Scorecard style checks, whether tests exist and pass, lint and typecheck configuration, lockfile consistency, runtime pins, committed secrets, branch protection, and AI agent readiness (AGENTS.md or CLAUDE.md, size and accuracy). It runs get-started-stinger in assess-only mode: where get-started would create something, a finding names the exact step that would fix it. It produces findings.jsonl, metrics.json and notes.md for 00-foundation/ under the Audit My Code contract 1.0 and changes nothing in the audited repository.

When to use

  • The orchestrator dispatches the Foundation dimension for any tier (foundation, vibe, basic, full, mario)
  • "Is this repo healthy?", "do we have CI and tests?", "will an AI agent be able to work in this repo?"
  • Before a security or quality audit, to learn whether the build, tests and lockfile are sound enough to audit

When not to use

  • Setting the repository up or fixing what the audit finds: that is get-started-stinger (writes files) or the mario tier's remediation step
  • Vulnerability analysis, exploitability, secret rotation: security-stinger and security-wasp-drone
  • Duplicate, dead or bloated code: code-bloat-wasp-drone
  • Implementation versus PRD checks: quality-stinger
  • CI pipeline design depth: ci-release-stinger; detailed GitHub settings scoring across eight dimensions: github-repo-health-stinger
  • README authorship: readme-writing-stinger

Procedure

  1. Read guides/00-scoping-and-read-only-rules.md first. It fixes the hard rules: never modify the audited repository, run project code only in the throwaway copy, GitHub access read-only, secrets redacted.
  2. Read <workspace>/intake.json. Check tools (python3, git, gh auth status) and record caps.
  3. Run scripts/foundation_scan.py --repo <repo> --gh --out <workspace>/00-foundation/raw/foundation_scan.json (drop --gh if gh is unavailable). It makes the file-presence and API checks and emits contract-shaped findings and measures.
  4. Follow guides 01 to 04 in order, reading only what the scanner cannot judge and resolving every finding tagged needs-drone-read: 01 Wasp Nest readiness, 02 CI, tests, lint and typecheck (run commands with scripts/run_in_copy.py), 03 dependencies, lockfiles and secrets, 04 repository governance.
  5. Follow 05 writing metrics and findings: write judgment.jsonl and measures-extra.json, run scripts/assemble_foundation.py until it validates, write notes.md, index the raw artifacts.
  6. Return a short report: verdict, counts by severity, measures in at-risk or critical, caps, output paths.

References map

PathLoad when
guides/00-scoping-and-read-only-rules.mdEvery run, first
guides/01-wasp-nest-readiness.mdLibrary, lock, agent file checks
guides/02-ci-tests-lint-typecheck.mdWorkflow review and running tests, lint, typecheck in the copy
guides/03-dependencies-lockfiles-secrets.mdLockfiles, update automation, runtime pins, env files, secret-shaped strings
guides/04-repository-governance.mdREADME, license, CODEOWNERS, branch protection, Scorecard view
guides/05-writing-metrics-and-findings.mdProducing and validating the output files
references/REFERENCE.mdMap of every reference file
references/foundation-checklist.mdEvery check id, default severity, owner, get-started step
references/get-started-assess-map.mdNaming the get-started step; what a healthy initialized repo has
references/measures-and-bands.mdBands for every metrics.json measure
references/scorecard-mapping.mdWhich Scorecard checks are approximated and how
references/gh-readonly-calls.mdBefore any gh call
references/detection-patterns.mdManual workflow, secrets, lockfile and agent-file checks
references/runtime-eol-table.mdEnd-of-life Node and Python pins
references/finding-templates.mdWriting judgment findings
references/research/distilled-foundation.mdVerifying a claim or resolving a conflict
Source research archive (not shipped with the plugin)Source-repository only; the shipped distillation summarizes it, do not require it
scripts/foundation_scan.pyStep 3: deterministic scan, read-only
scripts/run_in_copy.pyRunning project commands in the throwaway copy only
scripts/assemble_foundation.pyStep 5: validate and write the three output files
scripts/test_foundation.pyAfter any script edit: python3 scripts/test_foundation.py

Related drones and stingers

  • code-foundation-wasp-drone - The paired Drone that runs this Stinger and writes 00-foundation/.
  • audit-my-code-stinger - Owns the run contract, tiers and workspace this Stinger writes into.
  • get-started-stinger - Defines the baseline in assess mode; this Stinger never runs its write steps. Ships with the core Wasp Nest plugin, not this pack.
  • github-repo-health-stinger - Source of the read-only branch protection and settings checks; use it for the full eight-dimension GitHub hygiene report.
  • security-stinger - Receives handoffs for committed secrets and workflow injection.
  • dependency-audit-stinger - Deeper supply-chain triage beyond lockfile and update-tool presence.

Critical Directive

  • You must read all files and context contained within your skill.
  • In the event your core knowledge does not provide sufficient guidance you must make every attempt to search the internet, related knowledge base documentation files, and other available resources to supplement your knowledge prior to proceeding with your task.
  • Additional related skills can be found here:
    • get-started-stinger - Baseline for a correctly initialized repository; read in full before the first run.
    • github-repo-health-stinger - Read-only GitHub hygiene checks to borrow.
    • security-stinger - Where committed-secret and workflow findings go next.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Foundation Stinger AI skill do?

Read-only repo health audit: Wasp Nest setup, agent readiness, CI, tests, lint, lockfiles, secrets, governance. Writes contract-shaped foundation findings and measures. Never edits the repo.

Why use Code Foundation Stinger on TypingMind?

Because you install it once and use it with any model. Code Foundation Stinger is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Foundation Stinger in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/legioncodeinc/vibe-coding-tools/tree/main/plugins/code-audit-tools/skills/code-foundation-stinger. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Foundation Stinger?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Foundation Stinger?

As many as you like. As long as a model supports skills, you can use Code Foundation Stinger with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Foundation Stinger AI skill free?

Yes. It is published on GitHub by legioncodeinc under the AGPL-3.0-or-later license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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