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Audit Code

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aAAaqwq
audit-code

Run a two-pass, multidisciplinary code audit led by a tie-breaker lead, combining security, performance, UX, DX, and edge-case analysis into one prioritized report with concrete fixes. Use when the user asks to audit code, perform a deep review, stress-test a codebase, or produce a risk-ranked remediation plan across backend, frontend, APIs, infra scripts, and product flows.

Overview

PublisheraAAaqwq
RepositoryAGI-Super-Team
Skill nameaudit-code
Stars
98
Forks
23
Bundled files
4
LicenseMIT
Links
  • 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.

  • 4 bundled files

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

  • Open source

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

Installation

Install the Audit Code 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.
  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/aAAaqwq/AGI-Super-Team.git /tmp/AGI-Super-Team
mkdir -p .claude/skills
cp -r /tmp/AGI-Super-Team/skills/agent-skills-audit .claude/skills/audit-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Audit Code 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 Audit Code 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 Audit Code 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.

Audit Code

Overview

Run an expert-panel audit with strict sequencing and one unified output document. Produce findings first, sorted by severity, with file references, exploit/perf/flow impact, and actionable fixes.

Load references/audit-framework.md before starting the analysis.

Required Inputs

Collect or infer the following:

  • Audit scope: paths, modules, PR diff, or whole repository.
  • Product context: PRD/spec/user stories, trust boundaries, and critical business flows.
  • Runtime context: deployment model, queue/cron/background jobs, traffic profile, data sensitivity, and abuse assumptions.
  • Constraints: timeline, acceptable risk, and preferred remediation style.

If product context is missing, state assumptions explicitly and continue.

Team Roles

Use exactly these roles:

  • Security expert
  • Performance expert
  • UX expert
  • DX expert
  • Edge case master
  • Tie-breaker team lead

The tie-breaker lead resolves conflicts, prioritizes issues, and produces the final single report.

Workflow

Follow this sequence every time:

  1. Build Context Read code + product flows. Identify assets, entry points, high-risk operations, privileged actions, external dependencies, and "failure hurts" journeys.

  2. Build Invariant Coverage Matrix Before specialist pass 1, map critical invariants to every mutating path (HTTP routes, webhooks, async jobs, scripts):

  • Data-link invariants: multi-table relationships that must remain consistent.
  • Auth lifecycle invariants: disable/revoke semantics for sessions/tokens/API keys.
  • Input/transport invariants: validation, content-type policy, body-size/parse behavior.
  • Shape invariants: trees/graphs must reject cycles where applicable. Treat missing parity across equivalent paths as a finding candidate.
  1. Pass 1 Specialist Reviews Run role-specific analysis in this order:
  • Security
  • Performance
  • UX
  • DX
  • Edge case master Capture findings using the schema in references/audit-framework.md.
  1. Tie-Breaker Reconciliation Resolve disagreements:
  • Decide whether contested items are true issues.
  • Set severity and confidence.
  • Remove duplicates and merge overlapping findings.
  1. Cross-Review Pass 2 After edge-case findings, rerun specialists:
  • Security/Performance/UX/DX reassess prior findings and new edge-triggered scenarios.
  • Edge case master performs a final pass on residual risk after proposed mitigations.
  1. Final Report Publish one document from the tie-breaker lead with:
  • Findings first (ordered by severity, then blast radius, then exploitability).
  • Open questions/assumptions.
  • Remediation plan with priority, owner type, and verification tests.
  • Short executive summary at the end.

Quality Bar

Enforce these requirements:

  • Use concrete evidence with file references and line numbers where available.
  • Include reproduction steps for security/performance/edge findings when feasible.
  • Prefer actionable fixes over abstract advice.
  • Separate confirmed defects from speculative risks.
  • Mark confidence for each finding.
  • Run a cross-route consistency sweep: equivalent endpoints/jobs must enforce equivalent invariants.
  • For each High/Critical finding, include at least one focused regression test/check.

Safety and Policy Guardrails

Apply these guardrails while auditing:

  • Do not provide operational abuse instructions or exploit weaponization details.
  • Evaluate manipulative UX patterns as legal/trust/reputation risk, not as recommended growth tactics.
  • Prioritize user safety, system integrity, and maintainable engineering outcomes.

Output Format

Follow this response structure:

  1. Findings List only validated issues. Use the finding schema in references/audit-framework.md.

  2. Open Questions / Assumptions State missing context that could change priority or validity.

  3. Change Summary Summarize high-impact remediation themes in a few lines.

  4. Suggested Verification List focused tests/checks to confirm each major fix.

Runtime Heuristics

When the target stack is Bun + SQLite, apply the runtime-specific checklist in references/audit-framework.md (Runtime-Specific Heuristics (Bun + SQLite)) before finalizing findings.

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 Audit Code AI skill do?

Run a two-pass, multidisciplinary code audit led by a tie-breaker lead, combining security, performance, UX, DX, and edge-case analysis into one prioritized report with concrete fixes. Use when the user asks to audit code, perform a deep review, stress-test a codebase, or produce a risk-ranked remediation plan across backend, frontend, APIs, infra scripts, and product flows.

Why use Audit Code on TypingMind?

Because you install it once and use it with any model. Audit Code 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 Audit Code in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/agent-skills-audit. 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 Audit Code?

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 Audit Code?

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

Is the Audit Code AI skill free?

Yes. It is published on GitHub by aAAaqwq under the MIT 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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