mcpField
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iterate-pr

iterate-pr

github.com/getsentryDevelopment1.1k4.6k installsUpdated 5d ago
Repository

About iterate-pr

A pull request iteration skill for developers that fixes actionable CI failures and high- or medium-priority review feedback, then monitors checks. It distinguishes automated work from approval, draft, and merge-readiness gates that require reporting rather than action.

Key features

  1. 01Fetches PR checks and review feedback
  2. 02Prioritizes high- and medium-level feedback
  3. 03Guides root-cause fixes and local verification
  4. 04Monitors checks and feedback in a loop
  5. 05Reports human and draft readiness gates

Use cases

  1. 01Addressing CI failures on an open PR
  2. 02Working through actionable reviewer feedback
  3. 03Monitoring checks after pushing fixes
  4. 04Reporting when progress depends on human gates

MCP support

The skill uses authenticated `gh` and bundled scripts to inspect pull requests, retrieve checks and feedback, and post thread replies. It coordinates work on an MCP client only if one is stated; the input does not specify MCP functionality.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/getsentry/skills --skill iterate-pr

After installing, type/iterate-prin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

SPEC.md
agents/
openai.yaml
scripts/
fetch_pr_checks.py
fetch_pr_feedback.py
monitor_pr_checks.py
reply_to_thread.py

Details

From the project README

Iterate on PR Until CI Passes

Goal: fix actionable CI failures and high/medium review feedback. Stop and report human approval, draft-readiness, and merge-readiness gates.

Requires:

  • authenticated gh
  • uv
  • target repository root as cwd
  • skill-root-relative script paths, for example scripts/fetch_pr_checks.py

Bundled Scripts

ScriptRunOutput
scripts/fetch_pr_checks.pyuv run scripts/fetch_pr_checks.py [--pr NUMBER]JSON: pr, summary, checks, failure snippets
scripts/fetch_pr_feedback.pyuv run scripts/fetch_pr_feedback.py [--pr NUMBER]JSON buckets: high, medium, low, bot, resolved
scripts/monitor_pr_checks.pyuv run scripts/monitor_pr_checks.py [--pr NUMBER]terminal marker plus tab-separated checks
scripts/reply_to_thread.pyuv run scripts/reply_to_thread.py THREAD_ID BODY [...]JSON reply results

Check summary fields include failed, pending, actionable_pending, and human_gate_pending.

Monitor markers:

  • ALL_CHECKS_PASSED
  • CHECKS_DONE_WITH_FAILURES
  • NO_CHECKS_REGISTERED
  • DRAFT_PR_WITH_NO_CHECKS
  • CHECKS_BLOCKED_BY_REVIEW_GATE

Workflow

1. Identify PR

Run:

gh pr view --json number,url,headRefName,isDraft,reviewDecision

Stop when:

  • no PR exists
  • draft PR has no checks after monitor grace period: report DRAFT_PR_WITH_NO_CHECKS

Draft rule: inspect existing checks/feedback only. Do not mark ready for review unless asked.

2. Handle Feedback

Run uv run scripts/fetch_pr_feedback.py [--pr NUMBER].

BucketAction
highfix
mediumfix
lowask user which to address
botskip informational comments
resolvedskip

Feedback fix checklist:

  • verify root cause
  • search related code
  • fix all instances
  • for review_bot: true: fix real issues, explain false positives

Low-priority prompt format:

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 should I address? ("1,3", "all", or "none")
3. Check CI Status

Run uv run scripts/fetch_pr_checks.py [--pr NUMBER].

StateAction
failed > 0 and actionable_pending == 0fix failures
actionable_pending > 0wait; poll feedback while waiting
pending > 0 and actionable_pending == 0report CHECKS_BLOCKED_BY_REVIEW_GATE
no checks after grace periodreport NO_CHECKS_REGISTERED or DRAFT_PR_WITH_NO_CHECKS
all actionable checks passedrun post-CI feedback check

Wait for actionable review bots: sentry, warden, cursor, bugbot, seer, codeql. Do not wait for approval, isDraft, REVIEW_REQUIRED, Codecov, or informational bots.

4. Fix CI Failures

For each failure:

  1. read full log: gh run view <run-id> --log-failed
  2. trace from assertion/exception/lint rule to source
  3. state the cause before editing: "fails because X, affected by Y"
  4. search related call sites/patterns
  5. fix root cause, not symptom
  6. add focused test coverage when needed
5. Verify Locally, Then Commit and Push

Before commit:

  • test fix: rerun specific test
  • lint/type fix: rerun affected checker
  • code fix: rerun covering tests
  • local failure: fix before pushing
git add <files>
git commit -m "fix: <descriptive message>"
git push
6. Monitor CI and Address Feedback

Loop:

  1. run uv run scripts/fetch_pr_checks.py
  2. handle table in step 3
  3. while actionable_pending > 0, run uv run scripts/fetch_pr_feedback.py
  4. fix new high/medium feedback immediately
  5. if changed, verify, commit, push, restart loop
  6. otherwise sleep 30 seconds and repeat
  7. after checks pass, wait 10 seconds, fetch feedback once more
  8. if new high/medium feedback exists, return to step 4

Claude Code optional: run uv run scripts/monitor_pr_checks.py through MonitorTool with persistent: false; set timeout to normal repo CI duration. Restart the monitor after every push.

Exit Conditions

ExitConditions
Successactionable CI passed; post-CI feedback clean; low-priority choice handled
Ask usersame failure after 2 attempts; feedback unclear; infrastructure issue
Stopno PR; branch needs rebase; no checks; draft no-checks; only human gates remain

Fallback

If scripts fail, use gh CLI directly:

  • gh pr view --json number,url,headRefName,isDraft,reviewDecision
  • gh pr checks --json name,state,bucket,description,link
  • gh run view <run-id> --log-failed
  • gh api repos/{owner}/{repo}/pulls/{number}/comments

Comments

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