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-designgit 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-design)<a href="https://agentmods.dev/skills/codeaholicguy/ai-devkit/dev-design"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/dev-design/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-design"><img src="https://agentmods.dev/badge/skills/codeaholicguy/ai-devkit/dev-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 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]
- medium MCP Rug Pull · line 25 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 | $0.00044 | $0.00637 |
| Opus 5.5 | $0.00018 | $0.00255 |
| Sonnet 5.5 | $0.00009 | $0.00127 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
dev-design 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dev Design
Run the design review phase for configured AI docs features. Before changing docs or code, propose the concrete plan for this phase 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>. - Read existing requirements and design docs before changes.
- Ask until every material architecture, scope, validation, rollout, contradiction, trade-off, or open question is answered, explicitly deferred, or accepted as a named assumption.
- Ask one decision at a time, with why it matters, 2-3 viable options when useful, and a recommended answer.
- Do not approve or transition past design while material open questions remain.
- Use mermaid diagrams for architecture visuals where a diagram clarifies the design.
- If parent
dev-lifecycleestablished usable task tracing, emit design phase, progress, blocker/open-question, and next-step events pertask.
Review Design
Use for Phase 3.
- Run
npx ai-devkit@latest lint --feature <name>and review the design doc path it validates. If manual path resolution is unavoidable, first resolve.ai-devkit.jsonpaths.docs, falling back todocs/ai. - Search memory for relevant architecture patterns or past decisions.
- Cross-check against the latest matching requirements doc. Verify every goal, user story, and constraint has corresponding design coverage. Flag uncovered requirements.
- Review completeness: architecture, components, technology choices, data models, API contracts, design trade-offs, and non-functional requirements.
- Check usage-first design: APIs, CLI flows, UI flows, and docs should optimize for their caller/user, not implementation convenience.
- Screen design red flags: shallow modules, pass-through layers, temporal decomposition, leaked transport/storage/framework types, scattered validation, synchronized flags, and repeated conditionals where a domain model would fit.
- Resolve every gap, misalignment, open question, hidden assumption, or unresolved trade-off between requirements and design.
- Brainstorm alternatives for key architecture decisions and trade-offs before accepting the first approach.
- Prefer subtract-before-add sequencing: delete obsolete paths, consolidate redundant concepts, and narrow scope before adding new structure.
- Update the design doc with clarified decisions and chosen options.
- Store reusable architecture decisions in memory.
- If task tracing is available, record design coverage progress, next step, or blockers per
task. - Summarize requirements coverage, completeness assessment, updates made, and remaining gaps.
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 · 40 lines · 44 tokens per session scan A a6884e5eeb41
dev-design is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,647 stars, last pushed today), licensed Apache-2.0. It adds 44 tokens to every session and 637 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.