ai-assist-git-pr-review

REVIEW · 54
Registry indexed

Perform a standards-based code review on a GitHub Pull Request, then post the findings as inline review comments and mark the PR as 'Requested changes'. Reads all of the agents files that exist in the repository under review (AGENTS.md, .agents-docs/, CLAUDE.md on the PR's base b

Verified installs0
Stars88
Version1.0.0
Quality61/100 · Promising
Trust54/100 · Do not auto-install
Audit70/100 · Needs review

Supply asset profile

Coding and developer agents

Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.

Browse track

Scenario

GitHub automation

I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Maintenance

fresh

Pushed today

Risk

Needs review

License is unclear

GitHub quality

88

61/100 Quality · 62/100 Trust

Coverage tags

CodingGitHub automationcoding-agentsagent-skill

Review notes

License is unclear · Dependency or permission surface needs review

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
61

Useful candidate, but compare it with alternatives before adopting.

Trust

Do not auto-install
54

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

Audit

Needs review
70

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

88 GitHub stars

Repo activity

88 stars, 12 forks

Maintenance

Pushed today

License

Unknown

Install

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Install safety

standard package or runtime install path

Permission surface

secrets or environment access, shell or command execution

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • Repository license is unknown; clarify licensing for the skill.
  • License is unclear
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is unclear
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • GitHub automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Inspect repository metadata

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review
Policy
block
Human review
yes

Trust and risk

Trust
54/100
Audit
70/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Repository license is unknown; clarify licensing for the skill.
  • High-risk permission hints: Shell or command execution, Secrets or environment access
  • License is unclear

Agent safety v2

22/100 · Avoid automatic install

Blocked for auto-installblock

This skill should not be selected by an agent without explicit human security review.

Do not auto-install. Inspect the source, dependencies, and permission surface first.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Browser automation

Skill may drive a browser or interact with web pages.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • High-risk permission hints: Shell or command execution, Secrets or environment access
  • License is unclear

Install targets

Install this skill in your agent workflow

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-git-pr-review

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use ai-assist-git-pr-review in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-git-pr-review%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-git-pr-review/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use ai-assist-git-pr-review for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-git-pr-review/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

61/100

GitHub automation

Platforms

Claude Code

Audit report

Needs review · 70/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for GitHub automation

Prototype with this skill first; keep a fallback candidate ready.

61
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

GitHub automation

Trust label

Prototype first

Install path

Command ready

Use when

  • GitHub automation workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 61/100 quality profile
  • 3 OpenAgentSkill engagement events

review first

  • Repository license is unknown; clarify licensing for the skill.

Implementation path

  1. 1Install it in a sandbox agent and run one GitHub automation task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

54
OpenAgentSkill Trust Score

GitHub adoption

CHECK

88 GitHub stars

Stars/forks activity

CHECK

88 stars, 12 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

CHECK

Unknown

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Repository license is unknown; clarify licensing for the skill.
  • License is unclear
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 88 GitHub stars
  • Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Choose a stronger alternative or inspect the source manually before any install attempt.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

61
GitHub stars
88
Freshness
Today
Install ready
Yes
License
Unknown
Review before install: Repository license is unknown; clarify licensing for the skill.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: ai-assist-git-pr-review description: "Perform a standards-based code review on a GitHub Pull Request, then post the findings as inline review comments and mark the PR as 'Requested changes'. Reads all of the agents files that exist in the repository under review (AGENTS.md, .agents-docs/, CLAUDE.md on the PR's base branch) — the repo's full documented standards, not just any agents files the PR happens to change — checks the diff against them plus general best practices, and gates every write behind explicit approval. Use this skill whenever the user wants to code-review a PR, review a pull request, check a PR against standards, request changes on a PR, or gives you a GitHub PR link and asks for a review. Also triggers on: 'review this PR', 'code review', 'review PR', 'check this pull request', 'request changes', 'review against our standards', or a bare github.com/.../pull/<n> URL with review intent. This is a review-only skill — it never approves, merges, closes, or pushes code." argument-hint: "[PR URL] — e.g. 'https://github.com/org/repo/pull/42' or 'review https://github.com/org/repo/pull/42'" ---

# PR REVIEW

**Objective:** Review a GitHub PR against documented standards (its agents files) plus general engineering best practices, then — after your explicit approval — post the findings as inline review comments and submit the review as **REQUEST_CHANGES**.

**Role:** Senior reviewer writing for senior engineers. Read the diff deeply, ground every finding in evidence (a cited standard or a concrete code risk), and keep comments short and actionable. A good review reads like it came from a careful teammate, not a linter.

Start each response with `🔍 [PR Review — Step X: Name]` so the user can follow the flow.

## Safety Model

| Level | Actions | Behavior | |-------|---------|----------| | **Auto** | Read PR metadata, diff, changed files, agents files, existing review threads; analyze and de-duplicate | Execute immediately | | **Gated** | Post the review (inline comments + REQUEST_CHANGES) | Preview every comment → explicit approval → post → verify | | **Blocked** | Approve, merge, close, push, edit code, dismiss reviews | Never. This skill only *requests changes*. |

The single write in this skill is posting the review. Nothing reaches GitHub until the user has seen every comment and approved. This matters because a review is visible to the whole team and notifies the author — surprising them with unreviewed machine output erodes trust in the tool.

## Prerequisites

**gh CLI (BLOCKING — before any `gh` command):** run `gh --version` first. If it fails, the CLI isn't installed — tell the user to install and authenticate GitHub CLI (`gh auth login`), then stop. If `gh auth status` fails, prompt them to authenticate. Don't attempt other `gh` calls until both pass.

## Process

### Step 1: Get the PR link

The PR URL may be in `$ARGUMENTS`. If it isn't, ask: *"Which PR would you like me to review? Paste the GitHub PR link."* Don't guess or assume the current branch — this skill reviews an arbitrary PR by URL, which may live in a different repo than the current directory.

Parse the URL `https://github.com/<owner>/<repo>/pull/<number>` into `$owner`, `$repo`, `$number`. If it doesn't match that shape, ask the user to re-paste a full PR URL.

### Step 2: Load PR context

Fetch metadata (single call):

```bash gh api repos/$owner/$repo/pulls/$number \ --jq '{title, state, draft, headSha: .head.sha, baseRef: .base.ref, changedFiles: .changed_files, additions, deletions, author: .user.login}' ```

- **state != "open"** → stop: "PR #N is <state>. Reviews can only be posted on open PRs." (A closed/merged PR can't receive a REQUEST_CHANGES review.) - Capture `headSha` — you'll pin the review to it so comments land on the exact revision you reviewed. - If it's a draft, note it but continue (drafts can still be reviewed).

### Step 3: Gather the standards (the agents files)

The whole point of this review is conformance to *this repo's* documented standards, so read them from the PR's repo — not the local workspace, which may be a different project. **These are the agents files that exist in the repository, which define the standards — not merely the agents files the PR happens to modify.** A PR usually doesn't touch the agents docs at all; you still read the repo's full set to know the rules the changed code must follow. See `references/posting-review.md` §Gathering Agents Files for the exact `gh api` calls. In short:

1. List the **entire** repo tree on the PR's base branch and find every agents file present in the repo: `AGENTS.md`, `CLAUDE.md`, anything under `.agents-docs/`, and any `AGENTS.md`/`CLAUDE.md` in subdirectories. Do this against the full tree, independent of what the PR changed. 2. Read them. `AGENTS.md` files are usually a lightweight index that links to detailed docs under `.agents-docs/` — follow the links for any area the diff touches (e.g. if the PR changes C# code, read the C# coding-standards doc). 3. Distill a working checklist of concrete, checkable rules (commit format, naming, layering/wrapper boundaries, test structure, forbidden patterns, etc.). Keep the rules and *where each came from* so every finding can cite its source.

If the repo has **no** agents files, tell the user and offer to proceed on general best practices alone — the review is weaker without documented standards, so let them decide.

### Step 4: Fetch the diff and review

Get the changed files and the diff:

```bash gh pr diff $number --repo $owner/$repo ```

For any changed file where you need full surrounding context (not just the hunk), read it from the PR head: see `references/posting-review.md` §Reading a File at the PR Head. Don't review from hunks alone when a rule depends on context the hunk doesn't show (e.g. "private methods below public methods" needs the whole class).

**Evaluate each change against, in priority order:** 1. **Documented standards** from Step 3 — the primary bar. A violation of a written team rule is always worth flagging. 2. **General best practices** — obvious bugs, security issues (injection, secrets, auth gaps), missing null/error handling, race conditions, performance cliffs, and clear maintainability problems, even when no agents file mentions them.

**What NOT to flag (this matters — over-flagging erodes trust in the review):** - **Style the docs only *illustrate*, not *mandate*.** A code sample in an agents doc shows one way to write something; it is not a rule. Bracket-quoting object names, `BEGIN/END` wrappers, brace placement, and similar formatting choices are not findings unless a doc states them as an explicit requirement ("must", "always", a rule in prose — not just an example snippet). When in doubt, treat it as illustrative and stay silent. - **Personal-preference refactors** with no functional or documented basis. If you'd only be substituting your taste for the author's, don't comment. - **Speculative concerns** you can't ground in the diff, a cited standard, or a concrete risk. Every comment must trace to a rule or a real problem — if you can't name the basis, drop it.

A short review of real issues is worth far more than a long one padded with style opinions.

**Categorize each finding by severity** (this is what the user asked to see so they can triage NIT vs must-fix):

| Severity | Meaning | Examples | |----------|---------|----------| | **CRITICAL** | Must fix before merge — correctness, security, or data-loss risk; or a hard team rule that will break CI/deploy | SQL injection, leaked secret, null deref on a hot path, wrong commit format that the CI gate rejects, calling ServiceRepositories directly when the repo forbids it | | **WARNING** | Should fix — bug risk, missing validation/error handling, a documented convention violated, measurable perf issue | Swallowed exception, missing test for new logic, naming that violates the coding-standards doc, N+1 query | | **NIT** | Optional — style, readability, minor refactor with no functional impact | Import ordering, comment wording, a slightly cleaner idiom |

Anchor each finding to a specific `path` + `line` **that appears in the diff** (`side: RIGHT` for added/context lines, `LEFT` for deleted). This skill posts **inline comments only — no summary write-up of the PR.** A finding that doesn't map neatly to a changed line should be anchored to the nearest related changed line (e.g. attach a "missing test" note to the new file's `CREATE`/signature line); if it genuinely can't be tied to any changed line, drop it rather than writing a prose summary. See `references/posting-review.md` §Anchoring Rules.

Be disciplined about noise: don't invent findings to look thorough. If the PR is genuinely clean, it's fine to end up with only one or two comments — quality over volume.

### Step 5: De-duplicate against existing review threads

Before presenting anything, read the review activity that is **already on the PR** and classify each of your candidate findings as either **new** or **already-raised**. Other reviewers — human teammates and bots like GitHub Copilot and Devin Review — have often already raised the same points, and the author may have fixed them, replied with a rationale, or consciously declined. You must **not silently repost** an already-raised point (that relitigates a settled thread and signals you didn't read it) — but you must **not silently drop it either**. Instead, set already-raised findings aside and surface them to the user in Step 6 as items to review, so *they* decide whether the prior dismissal/resolution was actually correct. This step is mandatory, not optional. See `references/posting-review.md` §Gathering Existing Review Threads for the exact `gh api`/GraphQL calls. In short:

1. Fetch **all** prior review activity: inline review comments (`/pulls/$number/comments`), review summaries (`/pulls/$number/reviews`), and issue-level comments (`/issues/$number/comments`) — from every author, including bots (`Copilot`, `devin-ai-integration[bot]`, etc.) and the PR author's own replies. Also pull each thread's **resolved/outdated** status via GraphQL, which is a strong "already handled" signal. 2. For every candidate finding from Step 4, check whether an existing thread already covers the same issue on the same file/area. Classify it as **already-raised** if any of these hold (record *which* signal, *who* raised it, and *how* it was handled — replied/declined/resolved/outdated/fixed — you'll show this in Step 6): - A prior comment makes substantially the same point (even if worded differently or at a slightly different line). - The author (or anyone) **replied** to that thread dismissing it with a rationale or explaining it's intentional. - The thread is marked **resolved** or **outdated**, or the code it pointed at has since changed (a fix likely landed). 3. Everything else is a **new** finding. For each already-raised finding, also form a quick judgment: does the prior resolution look sound, or does it seem prematurely dismissed / not actually addressed? You'll present that assessment alongside the item so the user can decide whether to re-raise it.

Both buckets go to the user in Step 6 — **new** findings as proposed comments, **already-raised** findings as review items. Never auto-post an already-raised finding; only include it in the posted review if the user explicitly tells you to re-raise it.

### Step 6: Present findings for approval (GATED)

Show the user the complete set of inline comments before anything is posted. Use this structure:

``` 🔍 Review of PR #<n> — <title> Standards source: <which agents files informed this>

New findings — will be posted if approved (<count>): 1. [CRITICAL] <path>:<line> — <one-line finding> (cites: <standard or "best practice">) > <the exact comment body that will be posted> 2. [WARNING] <path>:<line> — ... 3. [NIT] <path>:<line> — ...

Already raised by others — NOT posted, for your review (<coun

Technical details

Version
1.0.0
License
Unknown
Last updated
Aug 23, 2026
Published
Aug 21, 2026

Decision snapshot

Fallback candidate

61
Ready
Prototype
Stage

recent repository activity

Audit

Install review

Install and adoption review

70
Needs review
Security
63/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for ai-assist-git-pr-review, ready for a manual X post.

Curator note
ai-assist-git-pr-review: Perform a standards-based code review on a GitHub Pull Request, then post the findings as inl...

88 stars

https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review?ref=x
Open X draft
Optional reply with install command
Listing + install path for ai-assist-git-pr-review:
https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review?ref=x

Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
jparkerweb
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This Registry indexed listing is attributed to jparkerweb but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-git-pr-review?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review)
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Author

J

jparkerweb

@jparkerweb

Platform fit

Health signals

GitHub stars
88
Quality score
36/100
Last GitHub push
Aug 22, 2026
Framework hints
Unknown
OpenAgentSkill views
3
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Do not auto-install

54
  • GitHub adoption88 GitHub starsCHECK
  • Stars/forks activity88 stars, 12 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenancePushed todayPASS
  • License clarityUnknownCHECK
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskcommand execution surface, credential or environment accessFIX