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 qingye-lab/rootloom --skill operating-code-reviewgit clone --depth 1 https://github.com/qingye-lab/rootloomWrote 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/qingye-lab/rootloom/operating-code-review)<a href="https://agentmods.dev/skills/qingye-lab/rootloom/operating-code-review"><img src="https://agentmods.dev/badge/skills/qingye-lab/rootloom/operating-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/qingye-lab/rootloom/operating-code-review"><img src="https://agentmods.dev/badge/skills/qingye-lab/rootloom/operating-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 | $0.00021 | $0.00386 |
| Opus 5.5 | $0.00008 | $0.00154 |
| Sonnet 5.5 | $0.00004 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
operating-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.
What it actually says
Code review
Review only. Do not modify files or execute external changes unless the user explicitly changes the task. Preserve unrelated work and respect the active access and approval rules.
Read the relevant diff and enough callers, consumers, contracts, or tests to assess its behavior. Treat the author's explanation and previous findings as leads, not proof. Load specialized References only for the affected surface:
- security or trust boundaries: security-review.md;
- persistent data or migrations: data-and-migration-review.md;
- dependencies, packaging, or release: dependency-and-release-review.md;
- rendered UI or interaction: ui-review.md.
For a defect repair, verify that the changed owner explains and fixes the original trigger. Challenge a completion claim with a concrete counterexample where useful; inspect an analogous implementation only when it could reveal the same failure. Consider cancellation, retries, partial failure, and compatibility when the changed behavior makes them relevant. Do not require every review to traverse every failure category or run a fixed test suite.
Report material findings by severity (Critical, High, Medium, Low), with an exact location, trigger and impact, supporting evidence, confidence, and the smallest concrete correction. Keep questions and optional improvements separate; style preferences are not defects.
If there are no material findings, say so and describe the reviewed scope and material gaps. Distinguish executed checks from suggested checks and do not claim unobserved success. Explain root-cause alignment for defect reviews; emit a machine-style status field only when an applicable reporting contract requires it. No empty sections or inapplicable checklist fields are needed.
What ships with it
5 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.
- 1mo ago Changed · -37 lines · -24 tokens per session 8a15fd80fc5f
- 1mo ago First seen · 72 lines · 45 tokens per session scan A 9da19fe3eded
operating-code-review is a skill published in the GitHub repository qingye-lab/rootloom (10 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 386 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 2026-08-31.
Other skills, from other repositories
readiness
Use when the user wants to analyze, audit, or assess their codebase for AI agent readiness. Also use for "readiness report", "how ready is my project", "analyze my codebase", "audit my repo", "check my setup", or "what should I improve".
template-comprehensive-assessment
Full checkout audit for the Research Project Template — tests, architecture, docs, manuscript, pipeline. USE WHEN user asks for comprehensive assessment, full repo review, health check across projects, audit everything, or pre-merge sanity sweep for template exemplars — even without naming docs/prompts or a skill. Not…
pr-sweep
Review every open PR with the code-reviewer agent and an adversarial review, apply the findings, and merge each one once CI is green. Use when asked to ship, sweep, or merge open PRs.
slop-check
LLM-judge slop & erosion scan of a diff, mirroring SlopCodeBench. Scores code on Erosion (verbosity, dead branches, redundant structure accumulated under iterative change) and Verbosity (unnecessary complexity), then reports per-category findings weighted toward code that EXTENDS existing modules. Use after…
agentic-code-review
Use when reviewing a diff, pull request, branch, or AI-generated code for correctness, security, regression, test, performance, and maintainability risks before merge.
repo-health-check
Use when auditing a repo before changes to find the smallest safe PR, quality risks, stale docs, missing tests, ignored-file gaps, or agent setup issues. Best first skill for unfamiliar codebases.