TaskFlow

SkillProductivity

Use when work should span one or more detached tasks but still behave like one job with one owner session, one return context, and durable flow state.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the TaskFlow skill

What this skill tells your AI

The instructions your AI receives, as published by qianleigood/crawclaw in skills-optional/taskflow/SKILL.md and read by ahel’s review.

Use TaskFlow when a job needs to outlive one prompt or one detached run, but still needs one owner session and one place to inspect or resume the work.

Use it for

  • multi-step background work with one owner
  • jobs that wait on detached ACP or subagent tasks
  • durable flow state between steps
  • child-task linkage with revision-checked mutations

Do not use it for

  • branching business logic
  • routing policy
  • domain-specific orchestration decisions

Keep those in the caller.

Canonical entrypoints

  • api.runtime.tasks.flows
  • api.runtime.tasks.flows.fromToolContext(ctx)
  • api.runtime.tasks.flows.bindSession({ sessionKey, requesterOrigin })

Lifecycle

  1. createManaged(...)
  2. runTask(...)
  3. setWaiting(...) when blocked on a person or external system
  4. resume(...)
  5. finish(...) or fail(...)
  6. requestCancel(...) or cancel(...)

Rules

  • Use managed TaskFlows when your code owns orchestration.
  • Treat stateJson as the persisted state bag.
  • Every mutating method after creation is revision-checked; always carry forward the latest revision.
  • Use runTask(...) instead of creating detached child tasks manually when you want parent orchestration.
  • Store only the minimum state needed to resume.

Signals

GitHub stars
30
Forks
1
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
taskflow-qianleigood
Source
github.com/qianleigood/crawclaw