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Deliver the User's Answer

submit_answer
Idempotent

Bring back what the user said to a question you raised with request_input, and pick the work up again. Call it the moment they answer, with their words — not your summary of them, and never a guess: you are the messenger here, and an answer you invented is worse than no answer at all, because it looks exactly like theirs. If they declined to answer, or nobody was there, do not call this: leave the question in their queue. Returns your runId and leaseToken so you carry on with the same attempt you paused, in the same context. If they answered somewhere else first — in the Weft app, on their phone — you get THAT answer back rather than an error, because what matters is that you continue with the right one.

Input Schema

NameRequiredDescriptionDefault
valueNoThe `value` of the option they picked, when they picked one
answerYesWhat the user said, in their words
questionIdYesFrom request_input

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
  2. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare idempotency, non-read-only, and closed-world; the description adds far more: the runId/leaseToken return values, that the same attempt and context are resumed, and the non-obvious edge behavior that an answer submitted elsewhere is returned instead of an error. It also warns against fabricating an answer, which is the key correctness failure mode.

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

Conciseness4/5

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

The core action is front-loaded, and the do-not-call condition and return semantics follow in a sensible order. The messenger/'an answer you invented is worse than no answer' line is slightly rhetorical for a tool description, but it earns its place by encoding the fidelity requirement.

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?

With no output schema, the description compensates by stating what is returned (runId and leaseToken) and how the run continues, plus the failure and alternate-client cases. Nothing an agent needs to call this correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so questionId, answer, and value are already documented, including 'in their words' and 'when they picked one' for value. The description reinforces the verbatim-fidelity requirement for answer but adds no format, length, or selector detail beyond the schema, so the baseline 3 applies.

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 names a concrete verb and resource — deliver the user's answer back to a pending request_input question and resume the paused run — and explicitly ties itself to the sibling tool request_input. An agent can distinguish it from every other sibling (which are task/sprint/project mutations) without opening the schema.

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

Usage Guidelines5/5

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

It gives an explicit trigger ('call it the moment they answer'), an explicit exclusion ('if they declined to answer, or nobody was there, do not call this: leave the question in their queue'), and covers the alternate-path case where the user answered in another client. When-to-use, when-not-to-use, and the alternative are all stated.

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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