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 DominikTobureto/awesome-grok-build --skill agentic-code-reviewgit clone --depth 1 https://github.com/DominikTobureto/awesome-grok-buildWrote 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/dominiktobureto/awesome-grok-build/agentic-code-review)<a href="https://agentmods.dev/skills/dominiktobureto/awesome-grok-build/agentic-code-review"><img src="https://agentmods.dev/badge/skills/dominiktobureto/awesome-grok-build/agentic-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/dominiktobureto/awesome-grok-build/agentic-code-review"><img src="https://agentmods.dev/badge/skills/dominiktobureto/awesome-grok-build/agentic-code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00642 |
| Opus 5 | $0.00019 | $0.00321 |
| Sonnet 5 | $0.00008 | $0.00128 |
| Haiku 4.5 | $0.00004 | $0.00064 |
Grade A, and why
agentic-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 12d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Code Review
Review like a senior engineer who wants the change to ship safely.
Grok Build Mode
- Use Plan Mode only if the review requires a fix plan. Pure review is read-only.
- Use subagents for independent passes on risky diffs:
correctness: behavior and edge cases.security: auth, permissions, secrets, injection, dependency risk.tests: coverage and missing regression tests.performance: complexity, queries, caching, bundle size.
- Arena-style review: if Arena Mode is available, compare independent review outputs and keep only findings with concrete failure paths. Otherwise synthesize subagent findings and dedupe.
- Human-in-the-loop: never auto-apply fixes unless the user explicitly asks. Findings first, fixes after approval.
Review Priority
- Correctness bugs.
- Security and privacy risks.
- Data loss, migrations, auth, payments, permissions, and concurrency.
- Missing or weak tests.
- Performance regressions.
- Developer experience and maintainability.
- Style only when it blocks comprehension or violates repo conventions.
Process
- Read the diff and the surrounding code.
- Identify the intended behavior from the issue, README, tests, or prompt.
- Check whether the implementation actually satisfies that behavior.
- Look for edge cases and failure modes.
- Verify test coverage maps to the risk.
- Run narrow verification only if the user asked for fix validation or the repo has cheap checks.
- Produce findings first. Keep summary short.
Finding Format
Use this format:
[P1] Title
File: path/to/file.ext:line
Problem: ...
Why it matters: ...
Suggested fix: ...
Severity:
P0: must fix before merge, production-breaking or data/security critical.P1: should fix before merge.P2: useful fix, not necessarily blocking.P3: polish or follow-up.
Example Prompts
Use agentic-code-review on the current diff. Findings first. Ignore style unless it creates real risk.
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.
- 12d ago First seen · 85 lines · 38 tokens per session scan A 1e379586d711
agentic-code-review is a skill published in the GitHub repository DominikTobureto/awesome-grok-build (61 stars, last pushed 19d ago), licensed MIT. It adds 38 tokens to every session and 642 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 2026-08-30.
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