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 tutur3u/platform --skill tuturuuu-review-commentsgit clone --depth 1 https://github.com/tutur3u/platformWrote 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/tutur3u/platform/tuturuuu-review-comments)<a href="https://agentmods.dev/skills/tutur3u/platform/tuturuuu-review-comments"><img src="https://agentmods.dev/badge/skills/tutur3u/platform/tuturuuu-review-comments/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/tutur3u/platform/tuturuuu-review-comments"><img src="https://agentmods.dev/badge/skills/tutur3u/platform/tuturuuu-review-comments.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 | $0.00020 | $0.01078 |
| Opus 5 | $0.00010 | $0.00539 |
| Sonnet 5 | $0.00004 | $0.00216 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade A, and why
tuturuuu-review-comments 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 5d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tuturuuu Review Comments
Use this skill when the user asks to check, re-check, revalidate, fix, resolve, or commit pending/unresolved comments for a GitHub PR or review resource.
Core Rules
- Treat thread-aware review data as authoritative. Flat PR comments are context, but unresolved inline review threads decide what remains pending.
- Verify every comment against current code before changing anything. If a comment is stale, duplicated, non-actionable, or wrong, say so and draft a response instead of forcing a code change.
- After fixing and validating actionable threads, resolve the addressed review threads by default unless the user says not to.
- Do not reply on GitHub, push, or commit unless the user explicitly asks for that write action.
- If the user asks to "fix comments", interpret that as all unresolved, non-outdated, actionable review threads unless they narrow the scope.
- Keep unrelated working-tree changes intact. Include them in a commit only when the user explicitly asks to include them.
Resolve The Resource
- If the user gives a PR URL, use it directly.
- If they give
owner/repo#123, split it into repo and PR number. - If they refer to the current branch, run:
gh auth statusgh pr view --json number,url,headRefName,baseRefName,title,state
- Check out the PR only when fixes are requested:
gh pr checkout <number-or-url>
Run gh commands with network access if sandboxing blocks GitHub.
Fetch Thread-Aware Comments
Prefer the bundled script:
python3 <skill-dir>/scripts/fetch_review_threads.py --repo owner/repo --pr 123 > /tmp/pr123-review-threads.json
Use built-in summaries for active unresolved threads:
python3 <skill-dir>/scripts/fetch_review_threads.py --repo owner/repo --pr 123 --active-only --summary > /tmp/pr123-active-review-threads.json
jq -r '.counts.active_unresolved' /tmp/pr123-active-review-threads.json
jq -r '.review_threads[] | [.id, .path, (.line // 0), (.author // ""), .headline] | @tsv' /tmp/pr123-active-review-threads.json
What ships with it
2 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.
- 5d ago Changed · -20 tokens per session 5cc0937d91ee
- 8d ago First seen · 98 lines · 40 tokens per session scan A 0e84a77d6e50
tuturuuu-review-comments is a skill published in the GitHub repository tutur3u/platform (53 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 1,078 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 2026-09-03.
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