fix-pr

fix-pr is a skill for Claude Code, Codex from Codagent-AI/agent-skills. It costs 63 tokens per session (1,955 once invoked), scanned A, original, MIT.

A workflow for repairing a pull request, which is a proposed set of code changes for review. It gathers failed CI checks—automated build and test checks—and review comments, then coordinates a fix, validates it, and pushes the changes.

In plain words
What is it for?
Use it to fix CI failures, address code-review comments, validate the repairs, and push the updated branch.
Why use it?
It brings the information needed to fix a pull request into one process instead of making you inspect failed checks and review feedback separately.

Skill for Claude CodeCodex

Part of the codagent plugin — 27 skills shipped together

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.

agentmods
npx agentmods add skills/codagent-ai/agent-skills/fix-pr
Any agent
npx skills add Codagent-AI/agent-skills --skill fix-pr
Clone the repo
git clone --depth 1 https://github.com/Codagent-AI/agent-skills

Made for: Claude Code, Codex.

Or install codagent, the plugin that ships this one along with the rest of its 27 skills.

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 fix-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/codagent-ai/agent-skills/fix-pr.svg)](https://agentmods.dev/skills/codagent-ai/agent-skills/fix-pr)
Your own site
<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/fix-pr"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/fix-pr.svg" alt="Measured on agentmods" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,955 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00063 $0.01955
Opus 5 $0.00032 $0.00978
Sonnet 5 $0.00013 $0.00391
Haiku 4.5 $0.00006 $0.00196

Measured 4d ago against content hash 2ba2c6d757e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix-pr 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 4d 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/fix-pr/SKILL.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

codagent:fix-pr

Fix CI failures and review comments on the current branch's PR by dispatching a fixer subagent with all failure context, verifying the fix with the validator, and pushing.

Steps

  1. Gather CI failure context

    # Get PR details
    gh pr view --json number,url,headRefName,baseRefName
    
    # Get all CI check results
    gh pr checks --json name,state,bucket,link
    

    For each failed check (bucket = fail):

    • Extract the GitHub Actions run ID from the link field:
      • Pattern: /actions/runs/(\d+)/
    • Fetch failed logs:
      gh run view <run-id> --log-failed
      
    • Collect: check name, link, and log output
  2. Gather review comment context

    # Get repo info
    gh repo view --json owner,name
    
    # Get all reviews
    gh api "repos/{owner}/{repo}/pulls/{pr-number}/reviews?per_page=100"
    
    # Get unresolved inline review threads via GraphQL (includes resolution status)
    # IMPORTANT: Inline owner, repo, and PR number directly into the query.
    # Do NOT use GraphQL variables ($owner, $repo) — the $ signs get stripped by the shell.
    gh api graphql -f query='
      query {
        repository(owner: "<owner>", name: "<repo>") {
          pullRequest(number: <pr-number>) {
            reviewThreads(first: 100) {
              nodes {
                id
                isResolved
                comments(first: 10) {
                  nodes {
                    id
                    author { login }
                    path
                    line
                    body
                  }
                }
              }
            }
          }
        }
      }
    '
    
    • Filter reviews to latest state per reviewer
    • Collect CHANGES_REQUESTED reviews: author, body
    • From the GraphQL result, collect only threads where isResolved is false: thread id, comment id, author, file path, line, body
  3. Dispatch fixer subagent

    Use the fixer prompt from the ## Fixer Subagent Prompt appendix below.

Read the full file on GitHub · 294 lines

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. 4d ago First seen · 294 lines · 63 tokens per session scan A 2ba2c6d757e9

Subscribe to this mod's changes

fix-pr is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,955 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 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens