Unity-MCP connects AI coding agents to the Unity game engine through MCP, letting them work with the Unity Editor and running games. It is used by game developers to generate code, automate development and testing, debug projects, and add AI-driven behavior to games. The catalogue entries provide skills, instructions, an MCP integration, and settings for operating this workflow.
Borrowing it
Nothing to install: this file belongs to IvanMurzak/Unity-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/IvanMurzak/Unity-MCP/main/.claude/skills/github-pr-review-fix/SKILL.mdgit clone --depth 1 https://github.com/IvanMurzak/Unity-MCPWrote 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.
[](https://agentmods.dev/skills/ivanmurzak/unity-mcp/github-pr-review-fix)<a href="https://agentmods.dev/skills/ivanmurzak/unity-mcp/github-pr-review-fix"><img src="https://agentmods.dev/badge/skills/ivanmurzak/unity-mcp/github-pr-review-fix/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.
<a href="https://agentmods.dev/skills/ivanmurzak/unity-mcp/github-pr-review-fix"><img src="https://agentmods.dev/badge/skills/ivanmurzak/unity-mcp/github-pr-review-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.01837 |
| Opus 5.5 | $0.00010 | $0.00735 |
| Sonnet 5.5 | $0.00005 | $0.00367 |
| Haiku 4.5 | $0.00002 | $0.00184 |
Grade A, and why
github-pr-review-fix 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- github-pr-review-fix — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review PR Comments
Review unresolved comments on the GitHub pull request associated with the current branch. Validate each comment, then fix legitimate issues.
Step 1 — Identify the Pull Request
- If
$ARGUMENTScontains a PR number, use it. - Otherwise, detect the current git branch and find its open PR:
gh pr view --json number,url,headRefName,baseRefName - If no PR is found, stop and tell the user.
Step 2 — Fetch All Unresolved Review Comments
Fetch PR review comments (not issue-level comments) using the GitHub CLI:
gh api repos/{owner}/{repo}/pulls/{number}/comments --paginate
Filter to comments where the thread is not resolved. Group comments by thread (same in_reply_to_id or same path + line/original_line). For each thread, treat the first comment as the review request and subsequent comments as discussion.
Also fetch general PR comments (issue-level):
gh api repos/{owner}/{repo}/issues/{number}/comments --paginate
If there are zero unresolved comments, report that and stop.
Step 3 — Validate and Fix Comments in Parallel (Sub-agents)
For each unresolved comment or comment thread, spawn a sub-agent in parallel. Use model: "sonnet" for cost efficiency. Each agent validates the comment and, if legitimate, fixes it immediately in place.
Conflict avoidance: If multiple comments target the same file, run those agents sequentially (not in parallel) to avoid edit conflicts. Comments on different files run in parallel.
Sub-agent Prompt Template
You are a code review comment validator and fixer. Your job is to determine whether a PR review comment identifies a real issue, and if so, fix it immediately.
## Comment Details
- **Author**: {comment_author}
- **File**: {file_path}
- **Line(s)**: {line_range}
- **Comment**: {comment_body}
- **Thread context** (if any): {thread_replies}
- **Comment ID**: {comment_id}
## Phase 1 — Validate
1. Read the file referenced in the comment. Focus on the specific lines mentioned.
2. Read surrounding context (50 lines above and below) to understand the code fully.
3. Analyze whether the comment identifies a legitimate issue:
- Is the described problem actually present in the code?
- Is the suggestion an improvement or just a style preference?
- Does the comment apply to the current state of the code (it may already be fixed)?
- Is this a nitpick / optional suggestion vs. a real bug, logic error, or missing handling?
4. Decide: FIX or IGNORE.
- If IGNORE, skip to the report below.
- If FIX, proceed to Phase 2.
## Phase 2 — Fix (only if verdict is FIX)
1. Apply the minimal fix that addresses the comment. Do not refactor unrelated code.
2. Ensure the fix:
- Does not break surrounding logic
- Follows the existing code style and conventions
- Preserves all existing functionality
3. If the fix requires changes in multiple locations within the same file, make all changes.
4. If you are unsure whether a fix is safe, do NOT apply it — set verdict to NEEDS_MANUAL_REVIEW instead.
HARD CONSTRAINTS:
- Only modify the file(s) specified. Do not touch other files.
- Do not add comments explaining the fix in the code.
- Do not refactor or "improve" code beyond what the comment asks for.
- Keep changes minimal and surgical.
## Report
Return your result in this exact format:
VERDICT: FIX | IGNORE | NEEDS_MANUAL_REVIEW
CONFIDENCE: HIGH | MEDIUM | LOW
REASON: <1-2 sentence explanation>
SUMMARY: <1 sentence describing what was changed, only if VERDICT is FIX>
FILE: {file_path}
LINES: {line_range}
COMMENT_ID: {comment_id}
FIXED: YES | NO
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.
- 1mo ago First seen · 214 lines · 24 tokens per session scan A f250f93bf50b
github-pr-review-fix is a skill published in the GitHub repository IvanMurzak/Unity-MCP (4,515 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 1,837 once invoked, about $0.0001 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.
Other skills, from other repositories
git-workflow
Branching and review conventions.
zen-comprehensive-review
Orchestrate a multi-model code review: spawn 3 review subagents, merge findings. In PR mode, posts GitHub PR comments with reactions. In local mode, outputs findings directly. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.
unity-csharp-standards
Apply Unity-specific C# standards that preserve readability, testability, and safe engine integration.
gitlab-merge-request-review
Review and merge GitLab merge requests via the gitlab-api MCP server — by default the MRs assigned to you or where you are a reviewer, optionally scoped to a project, group, or the whole instance. Read an MR, gate it on a green pipeline (pipeline → jobs → job log), then approve, accept/merge, or set…
repository-manager-candidate-certification
Understand and verify a branch candidate's and a sealed generation's certification state — the Candidate/Generation lifecycle vocabulary, the validation-stage/evidence model, and the rmconceptsverifycandidate / verifygeneration marker-collision checks — before trusting a merge-queue outcome as landable. This is the…
pr-reviewer
Review a requested pull request, branch diff or completed task against its actual scope, source and checks. Prepare evidence and comments; post or record a human verdict only when explicitly authorized.