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 joaquimscosta/arkhe-claude-plugins --skill resolving-pr-issuesgit clone --depth 1 https://github.com/joaquimscosta/arkhe-claude-pluginsWrote 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/joaquimscosta/arkhe-claude-plugins/resolving-pr-issues)<a href="https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/resolving-pr-issues"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/resolving-pr-issues/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/joaquimscosta/arkhe-claude-plugins/resolving-pr-issues"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/resolving-pr-issues.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 | $0.00104 | $0.01531 |
| Opus 5.5 | $0.00042 | $0.00612 |
| Sonnet 5.5 | $0.00021 | $0.00306 |
| Haiku 4.5 | $0.00010 | $0.00153 |
Grade A, and why
resolving-pr-issues 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 yesterday.
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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent PR Issue Resolver
Resolve review suggestions using parallel verification and confidence scoring.
Core Principle: Never assume a review comment is correct. Verify every suggestion against actual code before acting.
Input Detection
Detect input mode from $ARGUMENTS:
- PR mode: argument is a number (
123) or containsgithub.com/starts withhttp— useghAPI - File mode: argument contains
/or.mdor file exists on disk — parse findings from file - No argument: show usage hint and stop
Phase 1 — Context Gathering
PR mode — launch 2 parallel Haiku agents:
Agent A — PR Metadata: Run gh pr view $ARGUMENTS --json number,title,body,baseRefName,headRefName,state,author,reviewRequests,statusCheckRollup and gh pr diff $ARGUMENTS. Return: PR summary, base/head branches, CI status, files changed.
Agent B — Comment Extraction: Fetch all review comments using both endpoints:
- Inline review comments:
gh api repos/{owner}/{repo}/pulls/{pr}/comments - General issue comments:
gh api repos/{owner}/{repo}/issues/{pr}/comments
Return structured list: comment ID, author, type (inline/general), file:line (if inline), body text, resolved status, whether it contains a suggestion code block.
File mode — launch 1 Haiku agent:
Parse the review report file. Extract each finding: description, file:line, category, suggested fix. Detect format from review/skills/code-review/ report template or other common review formats.
Skip conditions: If no unresolved comments/findings exist, report "Nothing to resolve" and stop.
Phase 2 — Parallel Verification
For each unresolved comment/finding, launch a parallel Sonnet agent (batched in groups of 5):
Each agent receives: the comment text, 50 lines of file context around the referenced line, the PR diff (or current branch diff in file mode), and the PR description.
Each agent returns:
Verdict: CONFIRMED | FALSE-POSITIVE | AMBIGUOUS
Category: Blocker | Bug | Code Quality | Style | Question
Confidence: 0-100
Evidence: {what was checked and found}
Suggested resolution: {specific code change or response text}
What ships with it
3 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.
- yesterday First seen · 136 lines · 104 tokens per session scan A e0a29e4d2c5d
resolving-pr-issues is a skill published in the GitHub repository joaquimscosta/arkhe-claude-plugins (21 stars, last pushed yesterday), licensed MIT. It adds 104 tokens to every session and 1,531 once invoked, about $0.0004 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 2026-10-16.
Other skills, from other repositories
pr-creator
Create well-structured pull requests with proper descriptions and labels.
dev-rc
The last gate before merge — QA, security audit, review and changelog, with objective pass conditions.
pr-autofix
When the user has PR review feedback to address, CI failures to fix, or wants to automatically resolve common PR issues. Use when the user says "fix the PR," "address review comments," "CI is failing," "fix the build," "autofix," "pr feedback," "resolve comments," "fix merge conflicts," or when a PR needs updates…
babysit
Watch a pull request or review cycle until it is ready to merge. Use when asked to babysit, monitor, or keep checking PR comments, reviews, and CI until all actionable issues are resolved.
github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
feedback-builder
Point Aeon at a service's /feedback endpoint - pull what agents reported (bugs, missing features), triage and cluster it, then build the best accepted request as a PR for a human to approve.