goal-pr

goal-pr is a skill for Claude Code, Codex from dyoshikawa/rulesync. It costs 74 tokens per session (1,469 once invoked), scanned A, original, MIT.

A workflow that repeatedly reviews a pull request, fixes serious findings, waits for checks, and merges it when it is clean.

In plain words
What is it for?
Use it to finish a pull request by addressing medium, high, or critical findings and confirming that GitHub Actions checks pass.
Why use it?
It removes the manual loop of reviewing, correcting, rechecking, and merging a pull request.

Skill for Claude CodeCodex

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

Good fit Use it to finish a pull request by addressing medium, high, or critical findings and confirming that GitHub Actions checks pass.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dyoshikawa/rulesync/goal-pr
About the project

Rulesync is a command-line tool that generates configuration for different AI development tools from a shared set of rules. Developers use it to keep instructions, commands, MCP settings, ignore files, subagents, and skills consistent across coding agents. Catalogue skills support workflows built around Rulesync.

dyoshikawa/rulesync · 1,549 stars · on GitHub · rulesync.dyoshikawa.com

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 dyoshikawa/rulesync --skill goal-pr
Clone the repo
git clone --depth 1 https://github.com/dyoshikawa/rulesync

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 goal-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/dyoshikawa/rulesync/goal-pr/github.svg)](https://agentmods.dev/skills/dyoshikawa/rulesync/goal-pr)
Your own site
<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/goal-pr"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/goal-pr/github.svg" alt="Measured on agentmods" height="20"></a>

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 goal-pr

Your own site · 80×15
<a href="https://agentmods.dev/skills/dyoshikawa/rulesync/goal-pr"><img src="https://agentmods.dev/badge/skills/dyoshikawa/rulesync/goal-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,469 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 $0.00074 $0.01469
Opus 5.5 $0.00030 $0.00588
Sonnet 5.5 $0.00015 $0.00294
Haiku 4.5 $0.00007 $0.00147

Measured 25d ago against content hash 6c96ca9be3f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

goal-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 25d 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.

.rulesync/skills/goal-pr/SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Goal PR

target_pr = the user's request

This skill drives a pull request all the way to merge. It repeatedly runs the review-pr skill, fixes every finding of severity mid or above, and merges the PR once a review round reports no mid-or-above findings.

0. Determine and Prepare the Target PR

  1. If target_pr is provided (e.g. 123, #123, or a PR URL), use it.

  2. Otherwise, look for the PR of the current branch:

    gh pr view --json number,title,state,headRefName 2>/dev/null
    
  3. If no PR exists yet, create one (this satisfies the "PR is the goal" intent):

    • Use the commit-push-pr skill to commit the current changes, push the branch, and open a PR.
    • Then resolve target_pr to the freshly created PR number.

Confirm that the current local branch is the PR's head branch, because the fix phase below must commit and push fixes onto that branch. If they differ, ask the user how to proceed and stop.

1. Exit Condition

The loop exits when a single review round satisfies both of:

  • 0 findings of severity mid, high, or critical (only low findings, or none at all, may remain).
  • The PR's GitHub Actions checks are green — no check is fail or pending.

Set a hard safety cap of 10 iterations. If the exit condition is still not met at the cap:

  • If CI is green and every remaining finding is mid (no high or critical), merge anyway: record the remaining findings with the create-scrap-issue skill so they are tracked, then go to Section 3. mid findings are not merge blockers.
  • Otherwise (a high / critical finding remains, or CI is red), stop the loop and report the remaining findings and failing CI instead of merging.

2. Iteration Loop

Repeat the following until the exit condition is satisfied or the cap is hit.

2-1. Review Phase

Use the review-pr skill with target_pr. It assigns each finding a severity (low / mid / high / critical) and a sequential number, and also reports the GitHub Actions workflow status.

Read the full file on GitHub · 140 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. 25d ago Changed · +10 lines 6c96ca9be3f7
  2. 1mo ago First seen · 130 lines · 74 tokens per session scan A 4175774cea3c

Subscribe to this mod's changes

goal-pr is a skill published in the GitHub repository dyoshikawa/rulesync (1,549 stars, last pushed today), licensed MIT. It adds 74 tokens to every session and 1,469 once invoked, about $0.0003 per session on Opus 5.5. 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.