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 jaktestowac/awesome-copilot-for-testers --skill code-review-advancedgit clone --depth 1 https://github.com/jaktestowac/awesome-copilot-for-testersWrote 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/jaktestowac/awesome-copilot-for-testers/code-review-advanced)<a href="https://agentmods.dev/skills/jaktestowac/awesome-copilot-for-testers/code-review-advanced"><img src="https://agentmods.dev/badge/skills/jaktestowac/awesome-copilot-for-testers/code-review-advanced/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/jaktestowac/awesome-copilot-for-testers/code-review-advanced"><img src="https://agentmods.dev/badge/skills/jaktestowac/awesome-copilot-for-testers/code-review-advanced.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 | $0.00099 | $0.01818 |
| Opus 5 | $0.00049 | $0.00909 |
| Sonnet 5 | $0.00020 | $0.00364 |
| Haiku 4.5 | $0.00010 | $0.00182 |
Grade A, and why
code-review-advanced 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 9d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advanced Code Review
Use this skill when a review needs to go beyond style feedback and surface the real engineering risks in a change. It is built for complex pull requests, sensitive code paths, test automation suites, and refactors where a shallow review would miss important trade-offs.
When to Use
Use this skill when the user asks for things like:
- "review this PR critically"
- "audit this change for maintainability or security"
- "look for architectural issues, not just syntax problems"
- "review this test automation code for flakiness and long-term cost"
- "analyze whether this refactor is safe to merge"
Typical scenarios:
- large or multi-file pull requests
- legacy code audits
- high-risk changes in authentication, payments, permissions, data flows, or CI pipelines
- changes that add tests but may still reduce confidence
- code that technically works but appears expensive to maintain
Review Principles
- Evidence over intuition - every important finding should point to observable code, behavior, or missing coverage
- Risk over volume - a few high-signal findings are better than a long list of cosmetic remarks
- Context before judgment - understand intent, constraints, and surrounding patterns before recommending change
- Severity must mean something - blockers and high-risk findings must be clearly separated from notes and polish
- Actionable feedback only - explain why the issue matters and what the safer direction looks like
- Acknowledge uncertainty - if the review lacks context, say so explicitly instead of pretending certainty
Review Workflow
Follow the phases in order.
Phase 0: Frame the review
Before reviewing, establish:
- scope: whole repository, changed files only, or one subsystem
- review goal: correctness, readiness, architecture, security, test quality, or debt discovery
- change type: feature, bug fix, refactor, migration, test-only, or infrastructure
- constraints: release pressure, backward compatibility, legacy boundaries, compliance needs
What ships with it
4 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.
- 9d ago First seen · 199 lines · 99 tokens per session scan A 56ab3379ff8f
code-review-advanced is a skill published in the GitHub repository jaktestowac/awesome-copilot-for-testers (113 stars, last pushed 13d ago), licensed MIT. It adds 99 tokens to every session and 1,818 once invoked, about $0.0005 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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Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…
issue-creation
Trigger: issue creation, bug reports, feature requests, or issue approval. Create and triage GitHub issues from repository evidence.
sdd-tasks
Break an SDD change into implementation tasks. Trigger: orchestrator launches task planning for a change.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
cognitive-doc-design
Design docs that reduce cognitive load. Trigger: writing guides, READMEs, RFCs, onboarding, architecture, or review-facing docs.
skill-review-response
Use when a reviewer, CI bot, or another AI leaves feedback to address.