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 yeaight7/agent-powerups --skill review-comment-style-mininggit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/review-comment-style-mining)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/review-comment-style-mining"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/review-comment-style-mining/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/yeaight7/agent-powerups/review-comment-style-mining"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/review-comment-style-mining.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 | $0.00029 | $0.00337 |
| Opus 5.5 | $0.00012 | $0.00135 |
| Sonnet 5.5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
review-comment-style-mining 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
Review Comment Style Mining
When To Use
- User asks what writing feedback a PR received.
- Need to compare draft vs final docs, blog posts, prompts, or README text.
- Need recurring style lessons from reviewer comments.
Requirements / Checks
- Confirm
ghavailability and auth before fetching private PR data. - Ask before contacting GitHub or reading private repo content.
- Prefer bounded text formats:
.md,.mdx,.txt,.rst. - Cap large file diffs before sending to any model.
Workflow
- Identify PR URL or
owner/repoplus PR number. - Extract inline suggestions, plain feedback, and changed text file evolution.
- Separate mechanical edits from reviewer rationale.
- Compare first draft and final text by section.
- Group lessons by clarity, precision, tone, structure, grammar, and content.
- Return a concise style guide the author can reuse.
Safety Constraints
- Do not expose private PR content outside the local session without approval.
- Do not quote long proprietary text; summarize changes and cite file paths/permalinks when safe.
- Do not run broad GitHub fetches; scope to one PR unless user asks wider.
Validation / Done Criteria
- Output distinguishes explicit suggestions from inferred style lessons.
- Each lesson is tied to at least one review comment or text change.
- Large file content is truncated or summarized.
References
references/editorial-analysis-template.md
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 · 45 lines · 29 tokens per session scan A 758e79c91cd8
review-comment-style-mining is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 19d ago), licensed Apache-2.0. It adds 29 tokens to every session and 337 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 2026-09-14.
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