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 6BNBN/FlowPilot --skill code-reviewgit clone --depth 1 https://github.com/6BNBN/FlowPilotWrote 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/6bnbn/flowpilot/code-review)<a href="https://agentmods.dev/skills/6bnbn/flowpilot/code-review"><img src="https://agentmods.dev/badge/skills/6bnbn/flowpilot/code-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/6bnbn/flowpilot/code-review"><img src="https://agentmods.dev/badge/skills/6bnbn/flowpilot/code-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00031 | $0.00539 |
| Opus 5.5 | $0.00012 | $0.00216 |
| Sonnet 5.5 | $0.00006 | $0.00108 |
| Haiku 4.5 | $0.00003 | $0.00054 |
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 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex-Native PR Code Review
Use this workflow to review a pull request or diff with gh when available. Keep findings high-signal, actionable, and grounded in the actual change.
Source of truth
eferences/code-review-command.md
Review Workflow
-
Eligibility check
- Confirm the PR is still open and ready for review.
- Skip review if it is clearly out of scope, already handled, or obviously trivial.
-
Collect local guidance
- Identify the relevant AGENTS.md files for the touched paths.
- Treat those files as code-review guidance when applicable.
-
Summarize the change
- Use one fast subagent to summarize the PR and changed areas.
-
Run parallel review passes
- Launch independent review subagents with different lenses:
- conventions and AGENTS.md compliance
- correctness and bug risk
- history and git blame context
- prior PR or discussion context when relevant
- comments or invariants near the changed code
- Launch independent review subagents with different lenses:
-
Confidence-check findings
- Re-check each finding with a separate pass before surfacing it.
- Drop weak or speculative issues.
-
Filter for signal
- Ignore trivial lint, formatting, or typecheck issues that CI should catch separately.
- Ignore pre-existing issues unless the current PR makes them worse.
- Keep only the issues that matter to a senior engineer reviewing this change.
-
Comment or report
- If the user asked for a GitHub comment, use gh to post it.
- Otherwise, present the findings directly in the session.
Comment Format
Use this structure for final findings:
`markdown
Code review
Found 2 issues:
-
Brief description of issue
- Why it matters
- Evidence: file path or URL with full commit SHA when linking to GitHub
-
Brief description of issue
- Why it matters
- Evidence: file path or URL with full commit SHA when linking to GitHub `
If no issues remain after filtering:
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 · 78 lines · 31 tokens per session scan A 490ed168bc10
code-review is a skill published in the GitHub repository 6BNBN/FlowPilot (136 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 539 once invoked, about $0.0001 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
oma-refactor
Restructure existing code while preserving observable behavior. Use for targeted technical debt or hotspot work with characterization tests.
nobrainer-review
Use when the owner says nb-review, deep-audit, deep-code-review, or deep-autoreview; explicitly requests an evidence-gated CLOSEOUT, adversarial BUGHUNT or RELEASEGATE; or needs final findings filtered to verified actionable defects. Use nobrainer-build for ordinary implementation and correction work.
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
oma-scholar
Search academic literature and generate, validate, or compare Knows paper sidecars. Use for claim/evidence analysis and literature synthesis.
oma-hwp
Convert Hangul HWP, HWPX, or HWPML documents to Markdown with kordoc. Use for text, table, and image extraction from these formats.
issue
Use when starting a chain from a GitHub issue — turning an issue URL or number into a triaged, planned, dispatched, and reviewed pull request. Classifies the thread (bug → root-cause discipline, feature → plan chain, question → drafted reply), synthesizes a spec from the issue's own acceptance criteria, then runs the…