Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Borda/AI-Rig/plugin install bridgeWrote 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/borda/ai-rig/review)<a href="https://agentmods.dev/skills/borda/ai-rig/review"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/review.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00023 | $0.00290 |
| Opus 5 | $0.00012 | $0.00145 |
| Sonnet 5 | $0.00005 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
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 7d 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
Ask Codex to Review
Parse $ARGUMENTS: optional review instructions; optional model, effort, timeout-seconds, depth, run-id, workspace. Effort omitted: classify complete scope, pass selected level explicitly. Preserve caller-supplied level. Tiers: low = narrow mechanical change or settled fact; medium = bounded implementation, diagnosis, or review; high = cross-file, adversarial, architectural, or security judgment; xhigh = unusually broad and consequential; max = explicit caller request only.
Run python "${CLAUDE_PLUGIN_ROOT}/bin/bridge_call.py" review --task "<instructions>"; pass each supplied option separately. For quoted text you did not author, use scratch file + --task-file <path> instead of --task; mutually exclusive. Bridge runs read-only ephemeral general Codex execution with explicit adversarial-review prompt; default soft budget 300 seconds. Never resume review.
Return compact JSON envelope. Keep raw transcript at bridge-reported workspace-relative artifact path. Do not inline verbose peer details.
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.
- 7d ago First seen · 15 lines · 23 tokens per session scan A 21c04d74088d
review is a skill published in the GitHub repository Borda/AI-Rig (26 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 290 once invoked, about $0.0001 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
auto-test-code
A structured process for critically reviewing and testing software code. It records review findings, test plans, commands, results, and supporting files in a project workspace.
git-pr-review
A read-only reviewer for GitHub pull requests, which are proposed code changes submitted for review. It produces an evidence-based report about whether a pull request should be merged.
challenge
Use before a root-cause, done/verified claim, irreversible action, or 2nd-time fix reaches the owner (APEX or plain conversation); also fires at every eLicit/Verify gate. Not for code correctness (use sniper).
code-quality
Use when validating code quality after modifications -- SOLID compliance, DRY duplication, linter errors, architecture violations. Do NOT use for functional verification (run verification FIRST, then code-quality).
elicitation
Use when an expert agent self-reviews and self-corrects code after the Execute phase, before sniper validation (BMAD-METHOD elicitation techniques).
react-effects-audit
Use when auditing React or Next.js components for unnecessary or unsafe useEffect usage -- detects 9 anti-patterns from "You Might Not Need an Effect".