GitHub Issue Resolver

Workflow

Phase 1 — Issue Discovery

Trigger: User provides a GitHub repository (owner/repo).

Steps:

1. Validate repo against guardrails:

   python3 scripts/guardrails.py repo <owner> <repo>
   

   If blocked, tell the user and stop.

2. Fetch, score, and present issues using the recommendation engine:

   python3 scripts/recommend.py <owner> <repo>
   

   This automatically fetches open issues, filters out PRs, scores them by severity/impact/effort/freshness, and presents a formatted recommendation.

   Always use recommend.py — never manually format issue output. The script ensures consistent presentation every time.

   For raw JSON (e.g., for further processing):

   python3 scripts/recommend.py <owner> <repo> --json
   

⏹️ STOP. Wait for user to select an issue.

Phase 2 — Fixing

Trigger: User selects an issue.

Steps:

1. Lock the issue (one-at-a-time enforcement):

   python3 scripts/guardrails.py issue_lock <owner> <repo> <issue_number>
   

2. Read full issue thread including comments.

3. Clone the repo (Gate: notify):

   python3 scripts/sandbox.py run git clone https://github.com/<owner>/<repo>.git /tmp/openclaw-work/<repo>
   

4. Create a safe branch (Gate: auto):

   python3 scripts/sandbox.py run git checkout -b fix-issue-<number>
   

5. Explore codebase — read relevant files. For each file:

   python3 scripts/guardrails.py path <file_path>
   

6. Plan the fix — explain approach to user:

   ## Proposed Fix
   - Problem: [root cause]
   - Solution: [what changes]
   - Files: [list of files and what changes in each]
   - Estimated diff size: [lines]
   

⏹️ STOP. Wait for user to approve the plan before implementing.

7. Implement the fix (Gate: approve):
   • Apply changes
   • Check diff size: python3 scripts/guardrails.py diff <line_count>
   • Log: python3 scripts/audit.py log_action write_code success

Phase 3 — Testing

After implementing:

1. Find and run tests (Gate: notify):

   python3 scripts/sandbox.py run npm test   # or pytest, cargo test, etc.
   

2. If tests fail AND autoRollbackOnTestFail is true:

   • Revert all changes
   • Notify user
   • Suggest alternative approach

3. If no tests exist, write basic tests covering the fix.

4. Report results to user.

Phase 4 — Draft PR for Review (Approval REQUIRED)

⚠️ NEVER create PR automatically. Always ask first.

Do NOT dump full diffs in chat. For any non-trivial project, push the branch and let the user review on GitHub where they get syntax highlighting, file-by-file navigation, and inline comments.

1. Commit changes (Gate: approve):

   python3 scripts/sandbox.py run git add .
   python3 scripts/sandbox.py run git commit -m "Fix #<number>: <title>"
   

2. Show a change summary (NOT the raw diff) — keep it concise:

   ## Changes
   - **src/models.py** — Added field validation (title length, enum checks)
   - **app.py** — Added validation to POST endpoint, 400 error responses
   - **tests/test_app.py** — 22 new tests covering validation rules
   - 4 files changed, ~100 lines of source + ~150 lines of tests
   - All tests passing ✅
   

3. Ask explicitly: "Ready to push and create a draft PR?"

4. Only after user says "yes" (Gate: approve):

   python3 scripts/sandbox.py run git push -u origin fix-issue-<number>
   python3 scripts/sandbox.py run gh pr create --draft --title "..." --body "..."
   

   Note: PRs are always created as draft by default. The PR body should include a detailed description of all changes, test results, and link to the issue (Closes #N).

5. Share the PR link — user reviews on GitHub.

6. Unlock the issue:

   python3 scripts/guardrails.py issue_unlock
   

Scripts Reference

References

• references/quick-reference.md — GitHub API reference, scoring rubric, test commands
• references/guardrails-guide.md — Full guardrails documentation and customization