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 commands/ainative-build/skills/code-reviewgit clone --depth 1 https://github.com/ainative-build/skillsWhat 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 | $0.00033 | $0.00255 |
| Opus 5 | $0.00016 | $0.00128 |
| Sonnet 5 | $0.00007 | $0.00051 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
code-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 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.
What it actually says
/aif:code-review
Run the aif-code-review skill on the target described by $ARGUMENTS.
Read and follow ${CLAUDE_PLUGIN_ROOT}/skills/engineering/aif-code-review/SKILL.md in full, then
execute its workflow against $ARGUMENTS:
- Resolve the input mode and pin the fixed-point SHAs.
- Discover the spec source and build the shared context pack.
- Dispatch the three axes — in parallel isolated subagents here (Task tool available), one axis
each — using
${CLAUDE_PLUGIN_ROOT}/skills/engineering/aif-code-review/references/. - Aggregate into three separate sections (never merged or re-ranked) per
output-format.md. - Apply the verification gate before any pass/fixed claim.
For the parallel axes, spawn the aif:code-reviewer agent per axis with the axis brief + shared
context pack.
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 · 22 lines · 33 tokens per session scan A 3efb4ad6bb64
code-review is a command published in the GitHub repository ainative-build/skills (7 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 255 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
constraints
Define and enforce this project's quality bar — interview, sane defaults, CONSTRAINTS.md.
webperf
Run a web performance audit via the web-performance-auditor persona.
plan
Break work into small verifiable tasks with acceptance criteria and dependency ordering.
spec
Start spec-driven development — write a structured specification before writing code.
install
Add skills from GitHub repos, git URLs, or local paths.
audit-rules
Browse, enable, disable, and customize audit rules.