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 agentmods add skills/ivklgn/ai-kit/code-reviewernpx skills add ivklgn/ai-kit --skill code-reviewergit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00077 | $0.01076 |
| Opus 5 | $0.00039 | $0.00538 |
| Sonnet 5 | $0.00015 | $0.00215 |
| Haiku 4.5 | $0.00008 | $0.00108 |
Grade A, and why
code-reviewer 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 2d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer
Senior engineer conducting thorough, constructive code reviews that improve quality and share knowledge. Language-agnostic: apply the idioms and linters of the project under review, not a preferred stack.
When to Use This Skill
- Reviewing pull requests
- Conducting code quality audits
- Identifying refactoring opportunities
- Checking for security vulnerabilities
- Validating architectural decisions
Core Workflow
- Context — Read the PR description (or the diff against the base branch for local changes), understand the problem being solved. Checkpoint: Summarize the change's intent in one sentence before proceeding. If you cannot, ask the author to clarify.
- Structure — Review architecture and design decisions. Ask: Does this follow existing patterns in the codebase? Are new abstractions justified?
- Details — Check code quality, security, and performance. Apply the checks in the Reference Guide below. Ask: Are there N+1 queries, hardcoded secrets, or injection risks?
- Tests — Validate test coverage and quality. Ask: Are edge cases covered? Do tests assert behavior, not implementation?
- Feedback — Produce a categorized report using the Output Template. If critical issues are found in step 3, note them immediately and do not wait until the end.
Disagreement handling: If the author has left comments explaining a non-obvious choice, acknowledge their reasoning before suggesting an alternative. Never block on style preferences when a linter or formatter is configured.
For deep, focused passes beyond this broad review, the ai-kit specialists complement it: security-auditor (OWASP/dependency audit), architect-reviewer (macro-level design), language agents (golang-pro, typescript-pro, python-pro) for idiom-level review.
Reference Guide
Load detailed guidance based on context:
What ships with it
7 files 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.
- 2d ago First seen · 113 lines · 77 tokens per session scan A 813d37d739e7
code-reviewer is a skill published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 16d ago), licensed MIT. It adds 77 tokens to every session and 1,076 once invoked, about $0.0004 per session on Opus 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
semantix
Install and use the semantix memory kernel as a middleware in your agent: extract user preferences / workflows / experience from past sessions, retrieve and inject them on demand. One binary + your agent's own tools.
semantix-guide
Troubleshoot and configure Semantix capabilities: Skills (project/custom/global/builtin priority, discovery dirs), Commands (override order, /dir:file naming), Hooks (11 events, automatic project loading, matchers, timeouts), MCP (semantix-agent.toml + .mcp.json + plugin packages, autostart), plugin packages…
building-agents
Use when building or restructuring an LLM agent — provider adapter, tool calling, structured output, RAG, agent loop, eval gate, cost routing, tracing, MCP server — model-agnostic across OpenAI/Anthropic/Gemini/OSS so a model swap is a config change. NOT vector-store SQL alone (that is postgresdb) or service…
review-diff
Scan git diffs for project-specific anti-patterns. Triggers on: 'scan diff', 'check diff', 'anti-pattern check', 'pattern scan', 'review changes'.
review-full
Run a comprehensive multi-perspective code review on recent changes. Also triggers on 'is this secure?', 'security review', 'check for vulnerabilities', 'could this be exploited?' for security-focused review. Produces: GO/NO-GO verdict + findings table (Severity | Category | File:Line | Issue | Recommendation)…
save-diary
MUST use when user says 'save diary', 'write diary', 'diary entry', 'update diary', or 'document session'. Also auto-trigger at the end of any significant session (feature shipped, major bug fixed, architecture decision, new project started).