| name | evaluate |
| description | Deep-evaluate a GitHub repo and issue for contribution viability. Checks repo health, maintainer activity, competing PRs, merge speed, and produces a GO/NO-GO recommendation with scoring. |
| argument-hint | <owner/repo> <issue-number> |
/evaluate — Deep Issue Evaluation
You are running the WondrAIWork evaluation phase (Phase 02). Your job is to deeply assess whether a
specific issue is worth contributing to.
Step 1: Parse Arguments
The user should provide <owner/repo> <issue-number>. If missing, ask for them.
Example: /evaluate vercel/next.js 42846
Step 2: Run Evaluation Script
Execute the evaluation script:
bash ${CLAUDE_PLUGIN_ROOT}/scripts/evaluate.sh $ARGUMENTS
This produces a structured report with:
- Repository health metrics (stars, forks, language, license, activity)
- Issue details (title, state, labels, assignee, reactions, comments)
- Risk assessment (competing PRs, CLA requirements, archived status)
- Community PR merge speed (average days to merge for external contributors)
- Verdict (VIABLE / CAUTION / SKIP)
Step 3: Read Evaluation Methodology
Read the full evaluation framework:
cat ${CLAUDE_PLUGIN_ROOT}/methodology/02-evaluate.md
Step 4: Apply Go/No-Go Framework
Score each criterion as Pass/Fail:
| # | Criterion | Check |
|---|
| 1 | Repo merged external PRs in last 3 months | From merge speed report |
| 2 | Issue acknowledged by maintainer | Check issue comments |
| 3 | No competing active PR | From competing PRs section |
| 4 | CI is green on default branch | gh run list --repo REPO --branch main --limit 3 |
| 5 | Scope is estimable (hours, not weeks) | Your judgment based on issue |
| 6 | Required domain knowledge is available | Honest assessment |
| 7 | No disqualifying red flags | CLA issues, archived, etc. |
Decision rules:
- All 7 pass → Strong GO
- 1-2 fail → Conditional GO (note risks)
- 3+ fail → NO-GO (return to discovery)
Step 5: Calculate Weighted Score
Apply the scoring matrix from Phase 01:
- Impact (40%): Based on reactions, comments, issue severity
- Feasibility (35%): Based on scope, competition, technical complexity
- Visibility (25%): Based on repo stars, org reputation
Note: This is the Phase 02 preliminary score. It MUST be re-evaluated after Phase 03
(Understand) when the actual codebase complexity is known.
Step 6: Check for AI Contribution Policy
Check if the target repo has a policy on AI-assisted contributions:
gh api "repos/$1/contents/CONTRIBUTING.md" --jq '.content' 2>/dev/null | base64 -d | grep -i "ai\|copilot\|llm\|gpt\|claude" || echo "No AI policy found"
If they restrict AI contributions, flag this immediately.
Step 7: Present Evaluation Summary
Present a structured summary:
=== EVALUATION SUMMARY ===
Repo: owner/repo (★ stars)
Issue: #number — title
Score: X.X/5.0 (Impact: X | Feasibility: X | Visibility: X)
Verdict: GO / CONDITIONAL GO / NO-GO
Go/No-Go Checklist:
[x] External PRs merged recently
[x] Issue acknowledged by maintainer
[ ] No competing PRs ← RISK: 1 open PR found
...
Key Risks:
- ...
Recommendation:
- ...
Step 8: Suggest Next Steps
Based on the verdict:
If GO:
This issue looks viable. The next step is the Owner Briefing (Phase 02b). The owner briefing
presents the evaluation to the human owner for approval before any implementation begins. Use
/briefing to generate the briefing.
If CONDITIONAL GO:
This issue has risks: [list risks]. The owner should decide whether to proceed. Use /briefing to
present the evaluation with these risks highlighted.
If NO-GO:
This issue is not recommended. Reasons: [list]. Use /discover to find alternative targets.
Important Notes
- Competition check timing: Always re-check for competing PRs right before Phase 04
(Implementation), not just here
- Feasibility re-scoring: The Phase 02 score is preliminary. After Phase 03 (Understand),
re-score feasibility based on actual codebase complexity. If it drops below 4/10, abandon the
target.
- Owner Briefing is mandatory: Never proceed to Phase 03 without owner approval (Phase 02b)