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get_request_status

Check what happened to a request, and read any questions it asked back.

Intake is async (~5min cadence) - poll periodically. Read `next_action`:
"wait" (still processing), "answer_questions" (call answer_request with one
answer per question), "done" (see generated_roadmap_item_ids), "cancelled"
(terminal, no items), "failed" (see intake_failure_reason).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thread_idYes
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior1/5

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

The description uses read-oriented language ('Check', 'read') and describes a status retrieval, which implies a read-only operation. However, the annotations set readOnlyHint: false, indicating the tool may modify state. This is a direct contradiction. Additionally, the description provides no other behavioral disclosures beyond the async cadence and next_action semantics, which are useful but do not override the inconsistency.

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 description is concise: two sentences plus a compact enumeration of next_action values. It leads with the core purpose, then adds necessary operational details. The structure is efficient and easy to parse, though the list of values adds some length – still acceptable given the benefit.

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 explains the asynchronous nature, polling cadence, and the meaning of each next_action value, which is valuable even with an output schema. However, it fails to document the two required parameters, leaving a significant gap that could cause incorrect invocation. The output schema likely details return fields, so the description's focus on behavior is partially sufficient, but the parameter gap undermines completeness.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not explain project_id or thread_id at all. It mentions 'a request' but provides no context for what these identifiers are or how they relate. Since there is no parameter documentation in the schema either, the agent has no guidance on how to correctly supply these required fields.

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 clearly states 'Check what happened to a request, and read any questions it asked back' – a specific verb and resource. It goes further to enumerate the possible values of next_action, which distinguishes it from sibling tools like answer_request (which handles responding to questions) and refine_request. The purpose is unambiguous.

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 provides explicit usage context: 'Intake is async (~5min cadence) - poll periodically' advises when to call. It also gives conditional guidance on what to do based on next_action, including referencing the sibling tool answer_request for the 'answer_questions' case. While it doesn't explicitly say when *not* to use this tool, the polling guidance and follow-up actions make the intended usage clear.

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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