gh-pr-comment-resolution

gh-pr-comment-resolution is a skill for Claude Code, Codex from cisco-open/ai-harness-toolkit. It costs 63 tokens per session (569 once invoked), scanned A, original, Apache-2.0.

A GitHub workflow for finding pull-request review discussions, especially comments from GitHub Copilot, and closing those discussions after the related code has been fixed. It uses GitHub's command-line tool and API to identify each discussion thread.

In plain words
What is it for?
Finding the current pull request, fetching review threads, filtering Copilot comments, mapping them to files, applying fixes, and resolving completed threads.
Why use it?
It makes review comments traceable to specific files and ensures addressed discussions are properly marked as resolved.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Finding the current pull request, fetching review threads, filtering Copilot comments, mapping them to files, applying fixes, and resolving completed threads.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cisco-open/ai-harness-toolkit/gh-pr-comment-resolution
Install

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.

Any agent
npx skills add cisco-open/ai-harness-toolkit --skill gh-pr-comment-resolution
Clone the repo
git clone --depth 1 https://github.com/cisco-open/ai-harness-toolkit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for gh-pr-comment-resolution

README.md
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Your own site
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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.

agentmods 80×15 button for gh-pr-comment-resolution

Your own site · 80×15
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Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 569 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00063 $0.00569
Opus 5 $0.00032 $0.00284
Sonnet 5 $0.00013 $0.00114
Haiku 4.5 $0.00006 $0.00057

Measured 9d ago against content hash 7ac37a81b85e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

gh-pr-comment-resolution 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 9d 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.

skills/gh-pr-comment-resolution/SKILL.md · 65 lines

What it actually says

GH PR Comment Resolution

Overview

Use gh CLI + GraphQL to find Copilot review comments, map them to files, and resolve threads once the code is fixed. Provide a deterministic workflow for fetching comments, fixing issues, and closing review threads.

Workflow

1) Identify the PR and review threads

  • Get the PR number for the current branch:
gh pr view --json number,title,url,headRefName
  • Fetch review threads (includes thread ids for resolving):
gh api graphql -f query='query($owner:String!,$repo:String!,$number:Int!){repository(owner:$owner, name:$repo){pullRequest(number:$number){reviewThreads(first:50){nodes{id,isResolved,comments(first:20){nodes{id,body,author{login},path,position}}}}}}}' -f owner='<OWNER>' -f repo='<REPO>' -F number=<PR_NUMBER>
  • Optionally list classic review comments for easier scanning:
gh api repos/<OWNER>/<REPO>/pulls/<PR_NUMBER>/comments

2) Triage Copilot comments

  • Filter by author.login (e.g., copilot-pull-request-reviewer[bot]).
  • Group comments by path and map to files in the workspace.
  • For each comment, decide: fix in code or mark as already addressed.

3) Apply fixes

  • Make code changes in the referenced file(s).
  • If the file is vendored or patched, update the patch script instead of the vendored file.

4) Resolve review threads

  • Resolve each thread via GraphQL:
gh api graphql -f query='mutation($threadId:ID!){resolveReviewThread(input:{threadId:$threadId}){thread{id,isResolved}}}' -F threadId='<THREAD_ID>'
  • If a comment was already addressed, reply with context (optional) and resolve the thread.

5) Report back

  • Summarize the fixes and list any comments resolved as "already handled".
  • Suggest tests if relevant.

Notes

  • Prefer GraphQL for review thread resolution because REST review comments do not expose thread ids.
  • If reviewThreads exceed 50, paginate with reviewThreads(first:50, after: <cursor>).
Changes

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.

  1. 9d ago First seen · 65 lines · 63 tokens per session scan A 7ac37a81b85e

Subscribe to this mod's changes

gh-pr-comment-resolution is a skill published in the GitHub repository cisco-open/ai-harness-toolkit (11 stars, last pushed 13d ago), licensed Apache-2.0. It adds 63 tokens to every session and 569 once invoked, about $0.0003 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 2026-08-31.

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