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opencode-gpt-review

Run the review-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.

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dyoshikawa/webseek
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July 22, 2026 at 05:29
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name
opencode-gpt-review
description
Run the review-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-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 = $ARGUMENTS If no PR URL or PR number is provided, use the PR associated with the current branch as the review target. ## 1. Run review-pr via opencode Run the following command to have the github-copilot/gpt-5.4 model execute the review-pr skill via opencode. ```bash opencode run \ --model github-copilot/gpt-5.4 \ "review-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/ja
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