Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .claude/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add meshery/meshery-operator --skill iterate-pr -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .agents/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add meshery/meshery-operator --skill iterate-pr -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .cursor/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add meshery/meshery-operator --skill iterate-pr -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .gemini/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add meshery/meshery-operator --skill iterate-pr -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .github/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add meshery/meshery-operator --skill iterate-pr -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "iterate-pr" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/iterate-pr into .opencode/skills/iterate-pr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iterate-pr", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
iterate-pr
GitHub stars
151
Used in
7 other repos
Token cost
~2.2k tokens
SKILL.md length
976 words
Files
5 (incl. scripts)
Skills in repo
8
Repo updated
First seen
Licence
Apache-2.0
At a glance
Iterate on a PR until CI passes. An agent skill from meshery/meshery-operator.
Works in 8 steps: Identify PR → Gather Review Feedback → Handle Feedback by LOGAF Priority → …
You need to fix CI failures
SKILL.md covers Bundled Scripts, Workflow, Exit Conditions and Fallback
Runs Python scripts from its folder; calls uv, gh and git
What it does
Iterate PR is an agent skill from meshery/meshery-operator. 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.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `scripts/fetch_pr_checks.py`, `scripts/fetch_pr_feedback.py` and `scripts/reply_to_thread.py`).
It sits in Development, covering Pull requests and Failing and flaky tests. It works with Kubernetes. The repository describes itself as: Meshery Operator is a Kubernetes Operator that deploys and manages the lifecycle of two Meshery components critical to Meshery's operations of Kubernetes clusters. The licence is Apache-2.0.
When your agent uses it
You need to fix CI failures
Address review feedback
Continuously push fixes until all checks are green
Example prompts
“/iterate-pr”
Requirements
Python 3
Workflow steps
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 632cd41. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uv
gh
git
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
docs.astral.sh
develop.sentry.dev
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Iterate PR loads about 2.2k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 976 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~51
When it runs· the whole SKILL.md, loaded when a task matches
~2.2k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
Download SKILL.mdSave it as .claude/skills/iterate-pr/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
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.
Iterate on PR Until CI Passes
Continuously iterate on the current branch until all CI checks pass and review feedback is addressed.
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 ${HOME}/.agents/skills/iterate-pr.
Bundled Scripts
scripts/fetch_pr_checks.py
Fetches CI check status and extracts failure snippets from logs.
bash
uv run ${HOME}/.agents/skills/iterate-pr/scripts/fetch_pr_checks.py [--pr NUMBER]
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 via reply_to_thread.py)
scripts/reply_to_thread.py
Replies to PR review threads. Batches multiple replies into a single GraphQL call.
bash
uv run ${HOME}/.agents/skills/iterate-pr/scripts/reply_to_thread.py THREAD_ID "body" [THREAD_ID "body" ...]
Arguments are alternating (thread_id, body) pairs. The script sends the reply body without adding signatures, attribution, or sign-off text. Example:
bash
uv run ${HOME}/.agents/skills/iterate-pr/scripts/reply_to_thread.py \
PRRT_abc "Fixed the null check." \
PRRT_def "Replaced with path-segment counting."
Workflow
1. Identify PR
bash
gh pr view --json number,url,headRefName
Stop if no PR exists for the current branch.
2. Gather Review Feedback
Run ${HOME}/.agents/skills/iterate-pr/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 ${HOME}/.agents/skills/iterate-pr/scripts/reply_to_thread.py. Batch all replies for a round into a single call:
bash
uv run ${HOME}/.agents/skills/iterate-pr/scripts/reply_to_thread.py \
PRRT_abc "Fixed — description of change." \
PRRT_def "Not applicable — reason."
Reply format:
1-2 sentences: what was changed, why it's not an issue, or acknowledgment of declined items
Never add a signature, attribution line, tag, or vendor/model mention in replies
Keep replies tool-agnostic and identity-free
If the script fails, log and continue — do not block the workflow
4. Check CI Status
Run ${HOME}/.agents/skills/iterate-pr/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:
Read the log_snippet and trace backwards from the error to understand WHY it failed — not just what failed
Read the relevant code and check for related issues (e.g., if a type error in one call site, check other call sites)
Fix the root cause with minimal, targeted changes
Find existing tests for the affected code and run them. If the fix introduces behavior not covered by existing tests, extend them to cover it (add a test case, not a whole new test file)
Do NOT assume what failed based on check name alone—always read the logs. Do NOT "quick fix and hope" — understand the failure thoroughly before changing code.
Show full SKILL.md (340 more words)Show less
6. Verify Locally, Then Commit and Push
Before committing, verify your fixes locally:
If you fixed a test failure: re-run that specific test locally
If you fixed a lint/type error: re-run the linter or type checker on affected files
For any code fix: run existing tests covering the changed code
If local verification fails, fix before proceeding — do not push known-broken code.
bash
git add <files>
gh auth status -a
git commit --signoff -m "fix: <descriptive message>"
git push
Always add exactly one sign-off to each commit for the active authenticated GitHub user. Check gh auth status -a before committing to confirm the active account, use git commit --signoff, and do not add any other trailers, signatures, or tool attribution to commits or PR comments.
7. Monitor CI and Address Feedback
Poll CI status and review feedback in a loop instead of blocking:
Run uv run ${HOME}/.agents/skills/iterate-pr/scripts/fetch_pr_checks.py to get current CI status
If all checks passed → proceed to exit conditions
If any checks failed (none pending) → return to step 5
If checks are still pending:
a. Run uv run ${HOME}/.agents/skills/iterate-pr/scripts/fetch_pr_feedback.py for new review feedback
b. Address any new high/medium feedback immediately (same as step 3)
c. If changes were needed, commit and push (this restarts CI), then continue polling
d. Sleep 30 seconds (don't increase on subsequent iterations), then repeat from sub-step 1
After all checks pass, do a final feedback check: sleep 10, then run uv run ${HOME}/.agents/skills/iterate-pr/scripts/fetch_pr_feedback.py. Address any new high/medium feedback — if changes are needed, return to step 6.
8. Repeat
If step 7 required code changes (from new feedback after CI passed), return to step 2 for a fresh cycle. CI failures during monitoring are already handled within step 7's polling loop.
Exit Conditions
Success: All checks pass, post-CI feedback re-check is clean (no new unaddressed high/medium feedback including review bot findings), user has decided on low-priority items.
Ask for help: Same failure after 2 attempts, feedback needs clarification, infrastructure issues.
Stop: No PR exists, branch needs rebase.
Fallback
If scripts fail, use gh CLI directly:
gh pr checks name,state,bucket,link
gh run view <run-id> --log-failed
gh api repos/{owner}/{repo}/pulls/{number}/comments
We found 18 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in meshery/meshery-operator, which our catalogue first saw on October 7, 2026.
Iterate PR next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
Diagnose and unblock failed Dependabot pull requests in cloud-provider-azure by closing Kubernetes minor-version dependency bumps, classifying CI failures, syncing Go modules, retesting quota-flaked…
Diagnose and fix flaky tests tracked as open kind/flake issues in kubernetes-sigs/agent-sandbox — reproduce the flake, apply a minimal fix, and open a PR linking the issue.
Runs a gated finish-line checklist before committing a PlotJuggler PJ4 change: build proof, red-test triage, hooks, docs freshness and a diff self-review.
Iterate on a PR until CI passes. An agent skill from meshery/meshery-operator. Iterate PR is an agent skill from meshery/meshery-operator. Iterate on a PR until CI passes.
When should I use Iterate PR?
Iterate PR fits situations like: you need to fix CI failures; address review feedback; continuously push fixes until all checks are green.
How do I install Iterate PR in Claude Code?
Run `npx skills add meshery/meshery-operator --skill iterate-pr -a claude-code`. Or copy the skill folder (.claude/skills/iterate-pr in meshery/meshery-operator) into .claude/skills/iterate-pr in your project. Claude Code loads it when a task matches its description.
How do I install Iterate PR in Codex?
Run `npx skills add meshery/meshery-operator --skill iterate-pr -a codex`. Or copy the skill folder (.claude/skills/iterate-pr in meshery/meshery-operator) into .agents/skills/iterate-pr in your project. Codex loads it when a task matches its description.
Can I use Iterate PR in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add meshery/meshery-operator --skill iterate-pr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iterate-pr, .gemini/skills/iterate-pr, .github/skills/iterate-pr and .opencode/skills/iterate-pr in your project.
What does Iterate PR need to run?
Going by SKILL.md and its folder, Iterate PR needs Python for the scripts in its folder and the command-line tools its instructions call (uv, gh and git). Our summary lists: Python 3.
Does Iterate PR access the network?
SKILL.md names 2 domains. As links in the text: docs.astral.sh and develop.sentry.dev. This is read from the text; nothing was executed.
Is Iterate PR safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Iterate PR use?
Iterate PR is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Iterate PR use?
About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Iterate PR?
Skills that share tags, products or a category with Iterate PR: Unblock Dependabot PR (kubernetes-sigs/cloud-provider-azure, 294 stars), Fix Flakes (kubernetes-sigs/agent-sandbox, 4.2k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and PlotJuggler Ship Check (PlotJuggler/PlotJuggler, 6.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Iterate PR?
meshery (a GitHub organization) maintains it in meshery/meshery-operator, which has 151 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on September 21, 2026.
Source: meshery/meshery-operator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.