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 resolve-pr-feedbackgit 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/resolve-pr-feedback)<a href="https://agentmods.dev/skills/tobihagemann/turbo/resolve-pr-feedback"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/resolve-pr-feedback/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/resolve-pr-feedback"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/resolve-pr-feedback.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 | $0.00049 | $0.05219 |
| Opus 5.5 | $0.00020 | $0.02088 |
| Sonnet 5.5 | $0.00010 | $0.01044 |
| Haiku 4.5 | $0.00005 | $0.00522 |
Grade A, and why
resolve-pr-feedback 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 today.
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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resolve PR Feedback
Fetch unresolved review comments from a GitHub PR (inline threads, review-body observations, and issue-comment observations from the PR conversation), evaluate each one, fix or skip based on confidence, answer reviewer questions using the recalled rationale behind the change, and reply. Inline threads are answered with thread replies; issue-comment findings from people are answered with new PR conversation comments. Review-body findings, AI-reviewer issue comments, and the findings behind the head commit's failing checks flow through the same evaluate-and-fix pipeline; their outcomes land only in the summary.
Task Tracking
At the start, use TaskCreate to create a task for each step:
- Fetch comments and checks
- Triage already-addressed feedback
- Run
/interpret-feedbackskill - Split questions and change requests
- Run
/evaluate-findingsskill - Resolve ambiguities
- Run
/implement-findingsskill - Verify fixes
- Answer reviewer questions
- Wait for AI re-reviews and checks
- Run
/reply-to-pr-threadsskill - Run
/reply-to-pr-conversationskill - Summary
Step 1: Fetch Comments and Checks
Auto-detect owner, repo, and PR number from current branch if not provided. Then run ${CLAUDE_SKILL_DIR}/scripts/fetch-pr-data.sh, which handles full pagination (reviews, review threads, inner comment pages for long threads, issue comments, commits, the head commit's checks) and emits a single merged JSON document:
bash ${CLAUDE_SKILL_DIR}/scripts/fetch-pr-data.sh <owner> <repo> <pr_number>
Output shape:
{
"meta": { "title", "url", "headRefName", "headRefOid", "baseRefName", "body" },
"reviewThreads": [ { "id", "isResolved", "isOutdated", "comments": { "nodes": [ { "author", "body", "path", "line", "originalLine", "diffHunk" } ] } } ],
"reviews": [ { "author", "body", "state", "submittedAt" } ],
"issueComments": [ { "author", "body", "createdAt", "updatedAt", "url" } ],
"commits": [ { "commit": { "oid", "abbreviatedOid", "message", "committedDate" } } ],
"checks": [ { "name", "app", "state", "conclusion", "title", "detailsUrl" } ]
}
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.
- today Changed 14672217128b
- yesterday Changed · +14 lines ebe72003466a
- 2d ago First seen · 244 lines · 49 tokens per session scan A f869bbfb6e07
resolve-pr-feedback is a skill published in the GitHub repository tobihagemann/turbo (420 stars, last pushed today), licensed MIT. It adds 49 tokens to every session and 5,219 once invoked, about $0.0002 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 2026-11-11.
resolve-pr-feedback compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| resolve-pr-feedbacktobihagemann/turbo | Skill | 420 | today | MIT | A | 49 | Claude Code |
| pr-description-writermohitagw15856/pm-claude-skills | Skill | 1.5k | today | MIT | A | 80 | Claude Code, Codex |
| audit-prgtrabanco/agentic-workflow | Skill | 23 | today | MIT | A | 71 | Claude Code |
| neo-prBenknightdark/neo-skills | Skill | 7 | 2d ago | MIT | A | 60 | Claude Code, Codex |
| glab-mrserejaris/kimi-skills | Skill | 12 | 3mo ago | MIT | A | 92 | Claude Code, Codex |
| glab-stackserejaris/kimi-skills | Skill | 12 | 3mo ago | MIT | A | 79 | Claude Code, Codex |
| address-github-commentslingxling/awesome-skills-cn | Skill | 331 | 1mo ago | MIT | A | 27 | Claude Code |