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Agent skill

Audit Code Artifact

by NeuroAIHub in NeuroAIHub/BrainPilot

Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference.

AGPL-3.0Auto-check passed

Install Audit Code Artifact

skills CLI
$ npx skills add NeuroAIHub/BrainPilot --skill audit-code-artifact -a claude-code

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

GitHub CLI
$ gh skill install NeuroAIHub/BrainPilot audit-code-artifact --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/NeuroAIHub/BrainPilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/plugin-auditor/skills/audit-code-artifact .claude/skills/audit-code-artifact && 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
audit-code-artifact
GitHub stars
1.1k
Token cost
~477 tokens
SKILL.md length
213 words
Files
2
Skills in repo
59
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference.

  • Works in 6 steps: Trace critical values across data… → Verify that decision-relevant tunable… → Require existing numeric evidence that… → …
  • Claims depend on code
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Trained artifacts

What it does

Audit Code Artifact is an agent skill from NeuroAIHub/BrainPilot. Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference. Use when claims depend on code, trained artifacts, evaluators, or deployable entry points.

Its SKILL.md is about 480 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

The repository describes itself as: BrainPilot: Automating Brain Discovery with Agentic Research. The licence is AGPL-3.0.

When your agent uses it

  • Claims depend on code
  • Trained artifacts
  • Deployable entry points

Example prompts

  • “/audit-code-artifact”

Workflow steps

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

  1. Trace critical values across data loading, preprocessing, fitting, export, and
  2. Verify that decision-relevant tunable parameters live in machine-readable
  3. Require existing numeric evidence that the reference pipeline, exported model
  4. Require an existing clean-directory or evaluator-like smoke test using only
  5. Check for undeclared local modules, absolute workspace paths, environment
  6. Separate implementation correctness from scientific adequacy: a correctly

What it can do on your machine

Read from SKILL.md and the folder at commit 93f6855. 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.

    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

Audit Code Artifact loads about 477 tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 213 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~477

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 NeuroAIHub/BrainPilot at commit 93f6855, republished under its AGPL-3.0 licence (© NeuroAIHub). 213 words, ~477 tokens.

Download SKILL.mdSave it as .claude/skills/audit-code-artifact/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
audit-code-artifact
description
Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference. Use when claims depend on code, trained artifacts, evaluators, or deployable entry points.

Audit Code and Artifact

Inspect existing files and test outputs read-only. Do not execute the scientific pipeline or manufacture missing validation evidence.

Checks

  1. Trace critical values across data loading, preprocessing, fitting, export, and inference. Check defaults, branches, feature order, transforms, and manifest declarations against the scientific protocol.
  2. Verify that decision-relevant tunable parameters live in machine-readable configuration separate from the main implementation logic. Map each decision-relevant parameter from its stable name, value, unit, and provenance to the code that consumes it. Flag duplicated or unexplained values when they prevent a reviewer from determining which setting actually ran.
  3. Require existing numeric evidence that the reference pipeline, exported model or raw weights, and final entry point produce equivalent predictions on fixed samples within a stated tolerance.
  4. Require an existing clean-directory or evaluator-like smoke test using only collected artifacts and declared dependencies.
  5. Check for undeclared local modules, absolute workspace paths, environment variables, auxiliary files, incompatible versions, and entry-point assumptions.
  6. Separate implementation correctness from scientific adequacy: a correctly packaged artifact does not establish that its model or validation is suitable.

For a bounded parallel review, use code-reviewer for concrete implementation defects and repo-scout only when imports or artifact dependencies must first be mapped. Ask for evidence and candidate findings, not a verdict.

© NeuroAIHub, AGPL-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

SKILL.md and 1 other file in packages/plugin-auditor/skills/audit-code-artifact of NeuroAIHub/BrainPilot.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 93f6855

Compare with similar skills

Audit Code Artifact 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.

Audit Code Artifact compared with similar skills
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Audit Code Artifact this skillNeuroAIHub/BrainPilot1.1k—~477Automated safety check: PassAGPL-3.0
Dependency Scanningsickn33/agentic-awesome-skills47k1 repos~2.4kAutomated safety check: PassMIT
Artifacts Buildernexu-io/open-design100k—~347Automated safety check: PassApache-2.0
Dependency Checkruvnet/ruflo74k—~258Automated safety check: PassMIT
Web Artifacts Builderanthropics/skills180k41 repos~769Automated safety check: PassApache-2.0
Web Artifacts Buildernexu-io/open-design100k—~337Automated safety check: PassApache-2.0

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Questions about Audit Code Artifact

What does Audit Code Artifact do?

Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference. Audit Code Artifact is an agent skill from NeuroAIHub/BrainPilot. Audit scientific implementation, exported-model equivalence, dependency completeness, manifests, packaging, and isolated inference.

When should I use Audit Code Artifact?

Audit Code Artifact fits situations like: claims depend on code; trained artifacts; deployable entry points.

How do I install Audit Code Artifact in Claude Code?

Run `npx skills add NeuroAIHub/BrainPilot --skill audit-code-artifact -a claude-code`. Or copy the skill folder (packages/plugin-auditor/skills/audit-code-artifact in NeuroAIHub/BrainPilot) into .claude/skills/audit-code-artifact in your project. Claude Code loads it when a task matches its description.

How do I install Audit Code Artifact in Codex?

Run `npx skills add NeuroAIHub/BrainPilot --skill audit-code-artifact -a codex`. Or copy the skill folder (packages/plugin-auditor/skills/audit-code-artifact in NeuroAIHub/BrainPilot) into .agents/skills/audit-code-artifact in your project. Codex loads it when a task matches its description.

Can I use Audit Code Artifact 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 NeuroAIHub/BrainPilot --skill audit-code-artifact -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-code-artifact, .gemini/skills/audit-code-artifact, .github/skills/audit-code-artifact and .opencode/skills/audit-code-artifact in your project.

What does Audit Code Artifact need to run?

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

Does Audit Code Artifact 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 Audit Code Artifact 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 Audit Code Artifact use?

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

How many tokens does Audit Code Artifact use?

About 477 tokens (SKILL.md is roughly 1.9k 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 Audit Code Artifact?

Skills that share tags, products or a category with Audit Code Artifact: Dependency Scanning (sickn33/agentic-awesome-skills, 47k stars), Artifacts Builder (nexu-io/open-design, 100k stars), Dependency Check (ruvnet/ruflo, 74k stars) and Web Artifacts Builder (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Audit Code Artifact?

NeuroAIHub (a GitHub organization) maintains it in NeuroAIHub/BrainPilot, which has 1,060 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on October 2, 2026.

Source: NeuroAIHub/BrainPilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.