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 tobihagemann/turbo --skill reply-to-pr-conversationgit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/reply-to-pr-conversation)<a href="https://agentmods.dev/skills/tobihagemann/turbo/reply-to-pr-conversation"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/reply-to-pr-conversation/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/tobihagemann/turbo/reply-to-pr-conversation"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/reply-to-pr-conversation.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 | $0.00064 | $0.00719 |
| Opus 5.5 | $0.00026 | $0.00288 |
| Sonnet 5.5 | $0.00013 | $0.00144 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
reply-to-pr-conversation 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reply to PR Conversation
Draft a single reply that addresses a processed issue-comment list, confirm with the user, and post it as a new PR issue comment.
Step 1: Run /github-voice Skill
Run the /github-voice skill to load voice rules and the insider-vs-outsider detection.
Step 2: Compose the Reply
Use the processed-item list from conversation context. Each entry has: id, author, original comment body (to quote from selectively), category (fix, skip, answer, or clarify), and per-category payload.
Draft one reply that addresses every item as natural conversational prose. The output is a single piece of prose with flexible length and no rigid section structure.
Use the category to interpret each payload:
- fix: payload is a commit SHA. Mention "fixed in
<sha>" where it fits the flow, plus a brief note when the fix diverges from what the commenter suggested. - skip: payload is the skip reasoning. State it directly.
- answer: payload is answer text prepared upstream. Integrate it as the implementer's own words.
- clarify: payload is a user-directed question. Ask it as-is.
Quote selectively. Use > blockquotes only for the phrase being responded to. A single-topic reply quotes one sentence then responds; a multi-topic reply weaves quotes and responses together. Drop quotes entirely when @mentions plus context make the reply unambiguous.
Quote handling:
- Strip leading
>from quoted lines so nested blockquotes don't misattribute. - Replace fenced-code lines inside a quote with
> [code snippet]. - If the author login ends in
[bot], omit the suffix from the@mention.
Apply /github-voice rules. Match the conversation's length and tone. An acknowledgment with emoji is fine when the discussion calls for it; a multi-paragraph response is fine when the items warrant it.
Step 3: Confirm
Output the drafted reply as text for review:
**Draft comment**
<full comment body as it will be posted>
Then use AskUserQuestion to ask whether to post. Offer:
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 · 70 lines · 64 tokens per session scan A 9a75e79a4cee
reply-to-pr-conversation is a skill published in the GitHub repository tobihagemann/turbo (417 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 719 once invoked, about $0.0003 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 2026-08-30.
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