| name | assess-and-register |
| description | Activate before executing any substantive work that produces artifacts or requires multi-step execution (coding, data analysis, report generation, multi-agent chains). Guides you to check past epics for context, register a new Epic/Story/Task when none exists, mark tasks as doing before execution, and close them after completion.
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Assess & Register SOP
When to Use
Activate for any request that produces a physical artifact (code, data file, PDF, chart) or requires delegating to a sub-agent.
Skip this skill for:
- Pure conversation, greetings, or time queries
- Creating a reminder or regular work (they have their own tracking)
- User explicitly says "直接做" or "不用記錄"
- Simple one-shot lookup with no artifact output (e.g.
get_epics, get_user_profile)
Step 1 — Assess Past Records
Call get_epics(user_id=EXTRACTED_ID, status="all") to check all projects (active, completed, archived).
- Relevant epic found → call
get_epic_detail(epic_id) to read what was already done. Use this context when planning the current request (continue, extend, or correct prior work).
- No relevant epic → proceed to Step 2.
Step 2 — Register the Work
Timing: For single-step requests, register immediately before executing.
For multi-step requests requiring user plan confirmation (see multi-agent-chain skill), register after the user confirms the plan and before calling any specialist agent tool.
Create the project structure in order:
create_epic(user_id, title, description) — one epic per topic/project
create_story(epic_id, user_id, title, priority) — one story per major phase (e.g., "Backend API", "Data Analysis", "Report Generation")
create_project_task(...) — one task per concrete unit of work; all tasks are created with status=backlog
update_task_status(task_id_1, "doing") — mark only the first task as doing; all other tasks remain backlog until their turn
Then confirm to the user in one short line:
"已建立專案記錄,開始執行…"
Step 3 — Per-Task Completion (CRITICAL: close each task immediately, do not batch)
After each sub-agent returns a completion signal, run the acceptance-check skill before marking done:
- Activate
acceptance-check skill — verify all required output files exist
- Files confirmed → proceed to step 2
- File missing → skill requeues and retries; only proceed to step 2 after retry passes or task is marked
failed
add_task_comment(task_id, type="result", content="...") — record the output file path or result summary
update_task_status(next_task_id, "doing") — if a next task exists, mark it as doing now, then immediately call its matching specialist agent tool (<agent_name>(request='...'))
After all tasks are done:
4. update_story(story_id, status="done") — close the story