Metadata
| Status | done |
|---|---|
| Assigned | agent-732 |
| Agent identity | 3184716484e6f0ea08bb13539daf07686ee79d440505f1fdf2de0357707034c3 |
| Created | 2026-04-27T16:02:17.815934699+00:00 |
| Started | 2026-04-27T16:04:31.368568800+00:00 |
| Completed | 2026-04-27T16:07:32.068592776+00:00 |
| Tags | eval-scheduled |
Description
Quality Pass: Post-Triage Review
Review and optimize task metadata for newly created TUI chat redesign tasks before they enter execution.
Tasks to review
- research-tui-chat
- implement-tui-modal
- implement-tui-command
- implement-tui-tabs
- implement-tui-tab
- implement-tui-open
- implement-rename-remaining
- implement-tui-visual
- cleanup-sweep-stale
- integrate-tui-chat
What to do
For EACH task listed above:
1. Classify task type
Read the task via 'wg show '. Classify as one of: research, implementation, fix, design, test, docs, refactor.
2. Assign agent identity
Run 'wg agency stats --by-task-type' to see role performance by task type. Use the recommended role for each task's classified type. Fall back to overall Role Leaderboard if data is sparse. Apply: 'wg assign '.
3. Select model tier
From the same stats output, use the top-scoring model for the task type. Override heuristics:
- Simple/mechanical → haiku
- Standard implementation/test/research → sonnet
- Complex design / multi-system reasoning (e.g. modal-input rewrite, integrate-tui-chat) → opus Apply: 'wg edit --model '.
4. Release for execution
After assigning agent and model: 'wg resume '
Validation
- Every listed task has an agent assigned (check via 'wg show')
- Every listed task has a model set
- Every listed task is un-paused (status: open, not paused)
- Assignments are justified by evaluation data, not arbitrary
Depends on
Required by
- (none)
Log
- 2026-04-27T16:04:31.368572176+00:00 Spawned by coordinator --executor claude --model opus
- 2026-04-27T16:04:40.822858337+00:00 Starting quality pass: classify, assign agent, set model, resume for 10 TUI tasks
- 2026-04-27T16:07:23.952408300+00:00 Quality pass complete. All 10 TUI tasks: agent=Careful Programmer (f5143935, role 52335de1, 0.72 avg over 111 tasks). Models per complexity: opus×2 (modal rewrite, integration smoke), sonnet×7 (standard impl/research/refactor), haiku×1 (mechanical cleanup). All status=open (none paused). Justification: leaderboard shows Careful Programmer as the only proven implementer agent (Default Evaluator role 75d2fab8 scores higher but is for grading, not coding); per-task-type data is sparse (all 'other'), so used overall leaderboard + task-content heuristics from instructions.
- 2026-04-27T16:07:24.030040801+00:00 Validated: every task has agent assigned, model set, status=open
- 2026-04-27T16:07:32.068598457+00:00 Task pending eval (agent reported done; awaiting `.evaluate-*` to score)
- 2026-04-27T16:07:42.007804305+00:00 PendingEval → Done (evaluator passed; downstream unblocks)