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ClearTask Requirement Confirmation

AI Agent Updated 2026.08.30

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About this skill

Problem

When a request is vague, an agent may start too early and miss scope, inputs, deliverables, defaults, or external constraints. ClearTask is not meant to “start immediately”; it turns ambiguous intent into a confirmable, traceable task brief before execution.

How It Works

It follows a staged flow:

  • Stage 1 – Understand the request: structure the ask into request_summary, business_goal, scope, inputs, outputs, workflow_graph, assumptions, and open_questions, keeping assumptions separate from facts.
  • Stage 2 – Clarify critical gaps: ask only questions that would materially change execution, or record accepted_defaults instead of producing a long questionnaire.
  • Confirmation gate: present “requirement summary / details / your confirmation” in plain language and proceed only after the user explicitly agrees.
  • Stage 3 – Build the internal execution package: generate an AgentTaskGuidancePackage with expert guidance, execution advice, and checkable acceptance criteria; the full internal structure is not shown by default.

After execution, it reports what was completed, key defaults used, files or artifacts changed, self-check results, and remaining non-blocking issues.

Boundaries

It fits coding, documentation, planning, analysis, or product tasks that require a clear deliverable. It should pause when the requirement is unconfirmed, blocking questions remain, or the work touches many files, external systems, credentials, paid services, network access, or destructive operations. It is less suitable for quick exploratory analysis or workflows where the user expects output without confirmation.

Use Cases

  • Turn a vague backend request into scope, inputs, deliverables, and defaults, then let the user confirm before interface changes
  • Confirm readers, length, tone, and required API examples before drafting documentation that meets explicit acceptance criteria
  • Clarify characters, levels, asset inputs, and acceptance checks before generating game prototype code and scenes
  • Confirm metric definitions, time range, data source, and output format before producing a verifiable report

Best For

  • Engineers who need to write down scope and deliverables from informal product requests
  • Tech leads who want agents to confirm requirements before changing code
  • Data analysts who need fixed metric definitions and output formats before reporting
  • Developers who need to confirm readers, length, and API examples before documentation