---

name: iterate-pr description: Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle. risk: critical source: community

Iterate on PR Until CI Passes

Continuously iterate on the current branch until all CI checks pass and review feedback is addressed.

Requires: GitHub CLI (gh) authenticated.

Important: All scripts must be run from the repository root directory (where .git is located), not from the skill directory. Use the full path to the script via ${CLAUDE_SKILL_ROOT}.

Bundled Scripts

scripts/fetch_pr_checks.py

Fetches CI check status and extracts failure snippets from logs.

uv run ${CLAUDE_SKILL_ROOT}/scripts/fetch_pr_checks.py [--pr NUMBER]

Returns JSON:

{
  "pr": {"number": 123, "branch": "feat/foo"},
  "summary": {"total": 5, "passed": 3, "failed": 2, "pending": 0},
  "checks": [
    {"name": "tests", "status": "fail", "log_snippet": "...", "run_id": 123},
    {"name": "lint", "status": "pass"}
  ]
}

scripts/fetch_pr_feedback.py

Fetches and categorizes PR review feedback using the LOGAF scale.

uv run ${CLAUDE_SKILL_ROOT}/scripts/fetch_pr_feedback.py [--pr NUMBER]

Returns JSON with feedback categorized as:

• high - Must address before merge (h:, blocker, changes requested)
• medium - Should address (m:, standard feedback)
• low - Optional (l:, nit, style, suggestion)
• bot - Informational automated comments (Codecov, Dependabot, etc.)
• resolved - Already resolved threads

Review bot feedback (from Sentry, Warden, Cursor, Bugbot, CodeQL, etc.) appears in high/medium/low with review_bot: true — it is NOT placed in the bot bucket.

Each feedback item may also include:

• thread_id - GraphQL node ID for inline review comments (used for replies)

Workflow

1. Identify PR

gh pr view --json number,url,headRefName

Stop if no PR exists for the current branch.

2. Gather Review Feedback

Run ${CLAUDE_SKILL_ROOT}/scripts/fetch_pr_feedback.py to get categorized feedback already posted on the PR.

3. Handle Feedback by LOGAF Priority

Auto-fix (no prompt):

• high - must address (blockers, security, changes requested)
• medium - should address (standard feedback)

When fixing feedback:

• Understand the root cause, not just the surface symptom
• Check for similar issues in nearby code or related files
• Fix all instances, not just the one mentioned

This includes review bot feedback (items with review_bot: true). Treat it the same as human feedback:

• Real issue found → fix it
• False positive → skip, but explain why in a brief comment
• Never silently ignore review bot feedback — always verify the finding

Prompt user for selection:

• low - present numbered list and ask which to address:

Found 3 low-priority suggestions:
1. [l] "Consider renaming this variable" - @reviewer in api.py:42
2. [nit] "Could use a list comprehension" - @reviewer in utils.py:18
3. [style] "Add a docstring" - @reviewer in models.py:55

Which would you like to address? (e.g., "1,3" or "all" or "none")

Skip silently:

• resolved threads
• bot comments (informational only — Codecov, Dependabot, etc.)

Replying to Comments

After processing each inline review comment, reply on the PR thread to acknowledge the action taken. Only reply to items with a thread_id (inline review comments).

When to reply:

• high and medium items — whether fixed or determined to be false positives
• low items — whether fixed or declined by the user

How to reply: Use the addPullRequestReviewThreadReply GraphQL mutation with pullRequestReviewThreadId and body inputs.

Reply format:

• 1-2 sentences: what was changed, why it's not an issue, or acknowledgment of declined items
• End every reply with \n\n*— Claude Code*
• Before replying, check if the thread already has a reply ending with *- Claude Code* or *— Claude Code* to avoid duplicates on re-loops
• If the gh api call fails, log and continue — do not block the workflow

4. Check CI Status

Run ${CLAUDE_SKILL_ROOT}/scripts/fetch_pr_checks.py to get structured failure data.

Wait if pending: If review bot checks (sentry, warden, cursor, bugbot, seer, codeql) are still running, wait before proceeding—they post actionable feedback that must be evaluated. Informational bots (codecov) are not worth waiting for.

5. Fix CI Failures

For each failure in the script output:

1. Read the log_snippet and trace backwards from the error to understand WHY it failed — not just what failed
2. Read the relevant code and check for related issues (e.g., if a type error in one call site, check other call sites)
3. Fix the root cause with minimal, targeted changes
4. Find existing tests for the a