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 dev-reviewgit 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/dev-review)<a href="https://agentmods.dev/skills/codeaholicguy/ai-devkit/dev-review"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/dev-review/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/dev-review"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/dev-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 12 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]
- medium MCP Rug Pull · line 13 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 | $0.00047 | $0.00700 |
| Opus 5.5 | $0.00019 | $0.00280 |
| Sonnet 5.5 | $0.00009 | $0.00140 |
| Haiku 4.5 | $0.00005 | $0.00070 |
Grade A, and why
dev-review 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.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dev Review
Run final pre-push review for configured AI docs features. Before changing docs or code, propose the concrete review plan and wait for user approval unless the user already approved the exact phase plan.
Phase Contract
- Run
npx ai-devkit@latest lintbefore phase work. - If working on a named feature, run
npx ai-devkit@latest lint --feature <name>. - Check
git status -sbandgit diff --stat. - Read feature docs and relevant changed files before findings.
- Apply the
verifyskill before claiming readiness. - If parent
dev-lifecycleestablished usable task tracing, emit review phase, progress, blocker/finding, next-step, and final evidence/readiness events pertask.
Code Review
Use for Phase 9. Take a holistic review stance: findings first, ordered by severity, grounded in file/line references.
- Gather context: feature description, modified files, design docs, risky areas, tests already run.
- Verify design alignment by summarizing architectural intent and checking implementation matches.
- For each modified file, grep exported names to trace callers and dependents. Read relevant signatures, call sites, and type definitions.
- Check consistency against 1-2 similar modules.
- Search for existing utilities the new code could reuse or now duplicates. Flag near-matches honestly; do not force a wrong abstraction.
- Verify contract integrity at API, type, config, and schema boundaries.
- Check boundary discipline: external data is validated at edges, internal code is not littered with redundant guards, and transport/storage/framework types do not leak through domain APIs.
- Check reader load: needless layers, pass-through methods, broad shallow interfaces, mutable state scope, and unclear value ownership.
- Check domain fit: branch growth, synchronized flags, repeated shape assumptions, temporal decomposition, and missing state models.
- Check dependency health, including circular dependencies or version conflicts from new imports.
- Check breaking changes. For public/external APIs, recommend parallel change and deprecation over in-place mutation. For in-repo-only callers, all callers should be migrated and legacy APIs deleted.
- Check rollback safety, especially irreversible migrations or one-way data/state changes.
- Review file by file for correctness, logic, edge cases, redundancy, security, performance, error handling, and test coverage.
- Check cross-cutting concerns: naming conventions, documentation updates, missing tests, config/migration changes.
- Summarize blocking issues, important follow-ups, and nice-to-haves. Per finding include file, issue, impact severity, and recommendation.
- If task tracing is available, add blockers and set
blockedfor blocking findings; if review passes with final evidence, close the task pertask. - Complete final checklist: design match, no logic gaps, security addressed, integration points verified, tests cover changes, docs updated.
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 · 42 lines · 47 tokens per session scan A 367ce32411f9
dev-review is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,647 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 700 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
luna
Reviews code for objective correctness, security, and reliability.
max
Cleans up and improves existing code without changing behavior.
architect-review
Master software architect specializing in modern architecture.
mantis-plan
Formulates a targeted defensive security reviewing plan based on the active threat model and historical learnings. Use when starting a security review campaign to map the codebase boundaries and generate a roadmap (workspace/plan.json). Don't use for executing code reviews, writing test scripts, or patching code.
feedback-builder
Point Aeon at a service's /feedback endpoint - pull what agents reported (bugs, missing features), triage and cluster it, then build the best accepted request as a PR for a human to approve.
code-reviewer
Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with 2024/2025 best practices. Use PROACTIVELY for code quality assurance.