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Answer intake question

answer_question
Destructive

Answer the active applicant question with free text, optionally targeting a task_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoSigned hosted intake URL. Include it in every call to the hosted MCP endpoint.
textYes
task_idNo
session_idNo
access_tokenNoApplicant access token. Use it with session_id instead of url.
api_base_urlNoOptional Klarefi deployment URL for local stdio use. The hosted MCP endpoint does not accept this override.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already indicate destructiveHint=true and readOnlyHint=false, so the agent knows this is a mutating operation. The description adds minimal behavioral context beyond the parameters (free text, optional task_id) and does not contradict the annotations. It lacks details about workflow impact or reversibility, but the annotation covers the safety profile.

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?

A single, front-loaded sentence that conveys the action, the target, and the optional parameter with no wasted words. The structure is extremely efficient.

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

Completeness3/5

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

The description is minimally viable for a mutating tool with annotations, but it assumes the reader understands the 'active applicant question' workflow and does not mention return values, errors, or how the session/url context is established. With no output schema, a bit more context about the expected outcome would improve completeness.

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

Parameters4/5

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

With 50% schema description coverage, the description compensates by clarifying the two key parameters lacking schema descriptions: text ('free text') and task_id ('optionally targeting'). The remaining parameters (url, session_id, access_token, api_base_url) already have schema descriptions, so the description fills the gap for the undocumented essentials.

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 uses a specific verb ('Answer') with a clear resource ('active applicant question') and a distinguishing detail ('with free text'), which differentiates it from sibling tools like answer_fields. The optional task_id adds further scoping context.

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

Usage Guidelines3/5

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

The description implies the tool is for responding to an active applicant question and optionally targeting a task_id, but it does not explicitly state when to use this vs alternatives (e.g., answer_fields) or mention any prerequisites or exclusions. Some usage context is present but not fully developed.

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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