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 answer-reviewer-questionsgit 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/answer-reviewer-questions)<a href="https://agentmods.dev/skills/tobihagemann/turbo/answer-reviewer-questions"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/answer-reviewer-questions/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/answer-reviewer-questions"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/answer-reviewer-questions.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 | $0.00048 | $0.00450 |
| Opus 5 | $0.00024 | $0.00225 |
| Sonnet 5 | $0.00010 | $0.00090 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
answer-reviewer-questions 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 12d 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
Answer Reviewer Questions
For each reviewer question thread, recall the implementer's reasoning and compose a raw answer. The answers are plain text and feed into a downstream reply-drafting skill that applies voice rules and reply formatting.
Step 1: Collect Question Threads
Use the question threads from conversation context. Each thread has: thread id, file path, line (use originalLine when line is null), the reviewer's original comment, and the reconciled intent from /interpret-feedback.
If no question threads were provided, report that there are no questions to answer and stop.
Step 2: Answer Each Thread
For each thread:
- Run the
/recall-reasoningskill with<path>:<line>. It returns either recalled reasoning from a past transcript, or a fallback derived from reading the commit diff and surrounding code. - Compose a one-or-two-sentence answer from the returned reasoning. Quote or paraphrase the implementer's own words when the recalled reasoning explains the decision well.
- Do not mention Claude, transcripts, or that the reasoning was recalled. The answer reads as the implementer's own explanation.
Step 3: Output Answers
Output one block per thread:
**Thread <id>** (<path>:<line>)
<answer text>
_Grounding: derived from current code_
Include the _Grounding:_ line only when /recall-reasoning returned no transcript. Omit it when the answer is grounded in recalled reasoning.
Then use the TaskList tool and proceed to any remaining task.
Rules
- Do not load
/github-voiceor apply reply formatting. Downstream drafting applies voice rules when composing the actual reply. - When
/recall-reasoningreturned no transcript, still compose an answer from the current code and include the_Grounding:_line so the downstream drafter knows the answer has weaker grounding.
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.
- 12d ago First seen · 42 lines · 48 tokens per session scan A 0db99ef56460
answer-reviewer-questions is a skill published in the GitHub repository tobihagemann/turbo (402 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 450 once invoked, about $0.0002 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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