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Answer job question

answer_job_question

Resume a paused job with answers to the questions returned under pause. answers maps question IDs to {option_ids: [...], text: ...}; omitted questions use defaults. Relay consequential unanswered choices to the user unless those defaults were already authorized. Resuming may continue billed model work. Returns the next pause, terminal result or running status after wait_seconds; poll get_job_status if still running. Works with generate_sample clarification in both knowledge and source modes. See enricher://docs/documents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesPaused job ID.
answersNoMap of question id -> {option_ids: list[str], text: str | null}. Omit to resume with the planner's defaults.
wait_secondsNoHow long to wait for the job's next pause or completion before returning (0 = return immediately after resuming).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes well beyond the annotations by disclosing that resuming 'may continue billed model work', that omitted answers use defaults, and that consequential unanswered choices should be relayed unless already authorized. It also explains the return behavior and polling fallback, which the annotations do not cover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core action. Each sentence adds necessary information: answers structure, default behavior, cost implication, return behavior, polling alternative, and compatibility. There is no filler or redundant restatement of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, the description covers the input contract, default behavior, cost implications, return semantics, and follow-up polling. It also references enricher://docs/documents for further detail. Nothing critical appears missing for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds meaningful semantics: it defines the answers map structure as '{option_ids: [...], text: ...}', explains that omitted questions use defaults, and clarifies wait_seconds behavior by describing what is returned after the wait. This enriches the schema significantly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Resume a paused job with answers to the questions returned under pause.' This clearly differentiates the tool from siblings like cancel_job and get_job_status, and the title 'Answer job question' is expanded into a concrete action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states when to use the tool: when a job is paused and questions were returned. It also provides routing guidance by saying to 'poll get_job_status if still running' and mentions compatibility with generate_sample clarification. It lacks an explicit when-not-to-use statement, but the context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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