AI DevKit is a local-first control layer that gives multiple AI coding agents shared configuration, a terminal dashboard, cross-agent messaging, local memory retrieval, and reusable engineering workflows. It is for developers and teams supervising agents such as Claude Code, Codex CLI, Gemini CLI, OpenCode, Pi, Cursor, Copilot, or Devin. The catalogue entries are composable skills and plugin components used within that agent-management system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add codeaholicguy/ai-devkit --skill document-codegit clone --depth 1 https://github.com/codeaholicguy/ai-devkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/codeaholicguy/ai-devkit/document-code)<a href="https://agentmods.dev/skills/codeaholicguy/ai-devkit/document-code"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/document-code/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/codeaholicguy/ai-devkit/document-code"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/document-code.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 18 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00885 |
| Opus 5.5 | $0.00020 | $0.00354 |
| Sonnet 5.5 | $0.00010 | $0.00177 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
document-code scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- document-code — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Documentation Assistant
Build structured understanding of code entry points with an analysis-first workflow.
Hard Rule
- Do not create documentation until the entry point is validated and analysis is complete.
Workflow
- Gather & Validate
- Confirm entry point (file, folder, function, API), purpose, and desired depth.
- Verify it exists; resolve ambiguity or suggest alternatives if not found.
- Search for existing knowledge before analyzing:
npx ai-devkit@latest memory search --query "<entry point name or purpose>"
- Collect Source Context
- Summarize purpose, exports, key patterns.
- Folders: list structure, highlight key modules.
- Functions/APIs: capture signature, parameters, return values, error handling.
- Analyze Dependencies
- Build dependency view up to depth 3, track visited nodes to avoid loops.
- Categorize: imports, function calls, services, external packages.
- Exclude external systems or generated code.
- Synthesize
- Overview (purpose, language, high-level behavior).
- Core logic, execution flow, patterns.
- Error handling, performance, security considerations.
- Improvements or risks discovered during analysis.
- Create Documentation
- Normalize name to kebab-case (
calculateTotalPrice→calculate-total-price). - Create
docs/ai/implementation/knowledge-{name}.mdusing the Output Template — this is the source of truth. - Include mermaid diagrams when they clarify flows or relationships.
- Offer HTML Artifact
- After the markdown is written, ask the user once: "Also generate an HTML artifact for easier scanning? (y/N)".
- If yes, generate sibling
docs/ai/implementation/knowledge-{name}.htmlper the HTML Artifact spec. Regenerate from the markdown on subsequent runs; never hand-edit. - If no or no response, stop here — markdown alone is a complete result.
HTML Artifact
Generated only when the user opts in at step 6. A self-contained HTML file optimized for scanning, not reference reading. Complements the markdown — does not replace it.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 87 lines · 49 tokens per session scan A 9e0e4108e486
document-code is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,654 stars, last pushed 2d ago), licensed Apache-2.0. It adds 49 tokens to every session and 885 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
architecture-decision-records
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apify-youtube-transcript-scraper
Get YouTube captions, timestamped quotations, SRT/VTT and translated transcripts for videos, channels and playlists through the harshmaur/youtube-transcript-scraper Apify Actor.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
vuln-scanner
Audit trending repos for real security vulnerabilities and disclose responsibly - scan and route findings (PVR / dependency PR), re-submit queued advisories, and send armed email disclosures.
oss-upload
Upload local files to Tencent COS (oss.1024code.com CDN) using coscli. Use when user wants to upload a file to CDN/OSS, or deploy static assets.
autoresearch
Evolve a skill by generating variations, evaluating them, and updating the best version.