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mcpware
by mcpware

ask

Pose a question about your uploaded documents and get an answer with per-passage citations that map every claim to its exact source passage. Use after uploading documents.

Instructions

Ask a question about your documents. Returns an answer with per-passage citations mapping every claim to its source document and exact passage. This is the core tool — use it after uploading documents to a store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoGemini model to use (default: gemini-2.5-flash)
questionYesYour question about the documents
store_namesYesOne or more store resource names to search across

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does disclose a key non-obvious behavior: every claim in the answer is mapped to its source document and exact passage via per-passage citations. It does not cover error cases, auth requirements, or rate limits, but the core behavioral contract is clearly stated.

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?

Three short sentences with no filler. The primary action is front-loaded, followed by the distinct return-behavior detail, then the usage condition. Every sentence earns its place.

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?

For a simple 3-parameter tool with a fully described schema, the description covers what it does, what it returns, and when to use it. Nothing essential is missing for an agent to select and invoke this tool correctly. The corrupted context-signal text is external noise and does not affect the tool definition's completeness.

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 coverage is 100% — all three parameters (model, question, store_names) have descriptions and defaults where applicable. The description adds little parameter-level meaning beyond the schema, only the contextual precondition that documents should already be uploaded to a store. Baseline 3 is appropriate.

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 states a specific verb and resource: 'Ask a question about your documents.' It also specifies the return format — 'an answer with per-passage citations mapping every claim to its source document and exact passage' — making the tool's function unambiguous and distinct from generic search or listing tools.

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 gives clear usage context: 'This is the core tool — use it after uploading documents to a store.' This tells the agent when in the workflow to invoke it. It does not explicitly name alternatives or exclusion conditions, but none are provided in the sibling context.

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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