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Guitarmaniac24

GetABrain🧠 | Live Human-in-the-Loop MCP for AI Agents

get_responses

Read-only

Fetch a query's current status and submitted human responses instantly without waiting. Check progress on demand without blocking or retrying.

Instructions

One-shot read: fetch a query's current status and whatever human responses have been submitted so far, without waiting. Use this to check progress on demand, or after wait_for_responses reports "pending" if you want an immediate snapshot instead of polling again. Read-only, no cost, returns instantly (does not block or retry). Disambiguation: unlike wait_for_responses, this never delays or blocks waiting for more answers to arrive -- it just reports what exists right now, which may be fewer than required_responses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYesThe id returned by submit_query, identifying which query to read.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNo
responsesNo
required_responsesNo
completed_responsesNo
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds valuable context: 'no cost, returns instantly (does not block or retry)' and clarifies that the response may include fewer than required_responses. No contradictions with annotations.

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 three well-structured sentences, each adding unique value. Front-loaded with the core action, then usage guidance, then behavioral notes. No extraneous words.

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 one parameter, full annotations, and an output schema (not shown but referenced), the description covers all needed aspects: purpose, usage, behavior, and distinction from siblings. It is complete for an agent to select and invoke correctly.

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?

Schema coverage is 100% with a clear description of query_id. The description reinforces that the ID comes from submit_query, which adds context beyond the schema. A minor point: the description could mention the format or source more explicitly, but overall strong.

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 strong specific terms like 'One-shot read' and 'fetch...status and...responses,' clearly distinguishing from wait_for_responses. The verb 'fetch' combined with the resource 'query responses' leaves no ambiguity about the tool's function.

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?

The description explicitly states when to use this tool ('check progress on demand' or after wait_for_responses reports 'pending') and contrasts it with wait_for_responses by noting it never delays. This provides clear guidance on choosing between siblings.

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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