opencode-gpt-review

name	opencode-gpt-review
description	Run the `review-full-pr` skill on another model (github-copilot/gpt-5.4) via opencode, then thoroughly investigate and vet the resulting findings, and present only the valid ones to the user.
targets	["*"]

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.

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.

# 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

References

• https://opencode.ai/docs/ja