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Start the Agent Swarm Leader
Bulk, repeat, fan-out, or data-heavy work: write and run swarm scripts (inline `script-run`, named `script-upsert`, durable `launch-script-run`). Covers the script-vs-tool rubric, the authoring contract (`args` first, `ctx` second), the seed catalog, connections and secrets, `db_query`, and exposing a script as an API.
Mostrando SKILL.md
| name | work-on-task |
| description | Work on a specific task assigned to you in the agent swarm |
If no taskId is provided, call poll-task to get a new task.
Get task details: Call get-task-details with the taskId.
Recall relevant memories: Use memory-search with the task description before starting any work. Past learnings, solutions, and gotchas are indexed here.
Choose your approach based on the task type:
/researching/planning first, then /implementingWork on it, calling store-progress at each meaningful milestone (not just start and end — the lead monitors this).
Complete the task — see Completion below.
Call store-progress with:
status: "completed" + output: "<what you did and the result>". Output should be specific enough for the lead to assess without re-reading your work.status: "failed" + failureReason: "<what went wrong and what you tried>".Then reply "DONE" to end the session.
If interrupted by the user, adapt to their instructions. When resuming, call /skill:work-on-task <taskId> again to pick up where you left off.
If you're stuck after genuine effort (not just first failure), use /skill:swarm-chat to ask the lead for help or clarification. Don't spin — escalate.