Install in Claude Code
Copygit clone --depth 1 https://github.com/dyoshikawa/rulesync /tmp/opencode-gpt-review && cp -r /tmp/opencode-gpt-review/.rulesync/skills/opencode-gpt-review ~/.claude/skills/opencode-gpt-reviewThen start a new Claude Code session; the skill loads automatically.
Definition
SKILL.md
# GPT Review
Run the `review-full-pr` skill on another model (github-copilot/gpt-5.4) via
opencode, then thoroughly investigate and vet the resulting findings, extract
only the valid ones, and present them to the user.
## Prerequisites
- OpenCode must be installed.
- If not installed, tell the user it can be installed with `curl -fsSL https://opencode.ai/install | bash`.
- OpenCode must be configured to use GitHub Copilot.
- If not configured, tell the user to run `opencode` and use the `/connect` command to authenticate with GitHub Copilot.
## 0. Variable Definitions
PR_TARGET = the user's request
If no PR URL or PR number is provided, use the PR associated with the current branch as the review target.
## 1. Run review-full-pr via opencode
Run the following command to have the github-copilot/gpt-5.4 model execute the review-full-pr skill via opencode.
```bash
opencode run \
--model github-copilot/gpt-5.4 \
"review-full-pr スキルで ${PR_TARGET} をレビューしてください"
```
- `--model github-copilot/gpt-5.4`: Use the GPT-5.4 model.
Capture all output from the command.
## 2. Investigate and Vet the Review Results
For each finding in the review results obtained from opencode, investigate thoroughly using the following steps. Consider using subagents when appropriate.
### 2-1. Verify the Actual Code at the Finding's Location
- Based on the file path and line number in the finding, read the actual code to verify.
- Also check related context (related functions, classes, settings, etc.) that underlies the finding.
### 2-2. Judge the Validity of the Finding
Judge each finding from the following perspectives:
- **Fact check**: Does the finding match the actual code (is it not a hallucination)?
- **Impact**: Does the reported issue actually have an impact?
- **Context understanding**: Is it valid given the project's conventions and architecture?
- **Reproducibility**: Can the reported issue actually occur?
### 2-3. Classify the Finding
- **Valid**: A finding that is confirmed to be a real issue after checking the actual code.
- **Rejected**: A hallucination, misunderstanding, or a finding that is not an issue given the project context.
## 3. Present the Results
Output in the following format.
<Format>
# GPT Review Result
## Overview
- Review target PR: (PR URL or number)
- opencode model: github-copilot/gpt-5.4
- Total findings: N
- Valid findings: M
## Valid Findings
(List only findings judged as valid in the format below. If none, write "None".)
### Finding 1: (Title)
- **File**: `path/to/file.ext:line`
- **Problem**: (What is the problem)
- **Reason**: (Why it is a problem, based on the actual code you verified)
- **Severity**: "Must fix before merge" / "Can be deferred"
- **Recommended fix**: (Specific fix approach)
## Rejected Findings
(List rejected findings and the reasons concisely. If none, write "None".)
- ~~Finding~~: Reason for rejection
</Format>
## References
- https://opencode.ai/docs/jaMore from this repository
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