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dipseth

google-workspace-unlimited

fetch_document

Preview a stored tool response by its Qdrant point ID. Use after a semantic search to inspect a hit; returns the first 500 characters of content.

Instructions

Preview one stored tool response by its Qdrant point ID.

Use when: inspecting a hit returned by semantic_search. To find point IDs in the first place, use semantic_search; for the full untruncated content, call the fetch tool inside an execute block.

Behavior: read-only. Returns: tool name, service, timestamp, user, argument count, and the first 500 characters of stored content. Errors: 'Document not found' for unknown or expired point IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
point_idYesQdrant point ID (UUID) from a search result
user_google_emailNoUser's Google email (auto-injected by middleware)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavior: 'read-only', the exact return payload (tool name, service, timestamp, user, argument count, first 500 characters), and error behavior ('Document not found' for unknown or expired IDs). This exceeds the burden placed on the description.

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 concise and well-structured, using labeled sections (Use when, Behavior, Returns, Errors) that make it immediately scannable. Every sentence adds value, and there is no fluff.

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?

Even though an output schema exists, the description provides a complete picture: what the tool does, when to use it, what it returns, and how it errors. This is especially strong given the lack of annotations, making the tool fully understandable for an agent.

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%, including a clear definition for point_id and the auto-injected nature of user_google_email. The description adds no additional meaning beyond the schema, so the baseline of 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 clearly states the action ('Preview one stored tool response by its Qdrant point ID') with a specific verb, resource, and identifier. It also distinguishes itself from siblings by noting it works on results from semantic_search and defers full content to a different tool.

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?

Explicitly provides when to use ('inspecting a hit returned by semantic_search'), how to find point IDs ('use semantic_search'), and when to use an alternative ('for the full untruncated content, call the fetch tool inside an execute block'). This gives clear and complete usage guidance.

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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