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Fetch a resource

fetch
Read-only

Fetch the full content of a single resource by the id returned from search.

Returns the resource's id, title, full text, url, and metadata. This is the deep-research "fetch" entrypoint paired with search — both names are fixed by the ChatGPT/Claude connector spec, so they read more generic than the rest of the surface.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesA resource id returned by `search` (the `id` field of a search result).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
urlYes
textYes
titleYes
metadataNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedOutput schema / additionalProperties
      Removed value: -true
    • addedOutput schema / properties
      Added value: +{
      +  "id": {
      +    "type": "string"
      +  },
      +  "metadata": {
      +    "additionalProperties": true,
      +    "type": "object"
      +  },
      +  "text": {
      +    "type": "string"
      +  },
      +  "title": {
      +    "type": "string"
      +  },
      +  "url": {
      +    "type": "string"
      +  }
      +}
    • addedOutput schema / required
      Added value: +[
      +  "id",
      +  "title",
      +  "text",
      +  "url"
      +]
  2. Changed1 schema field changed
    • addedInput schema / properties / id / description
      Added value: +"A resource id returned by `search` (the `id` field of a search result)."
  3. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description adds context about returning full content and fields. It does not contradict annotations but also does not disclose additional behavioral traits like rate limits or error states.

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 two sentences plus a brief note, all front-loaded and non-redundant. Every sentence adds value with no wasted 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?

With an output schema present, the description adequately explains the tool's purpose and usage. It covers all necessary aspects for a simple fetch-by-id tool with good annotations.

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% and the parameter description already states it is an id from search. The description repeats this but adds no new semantics beyond the schema, so 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 clearly states the tool fetches full content of a single resource by id from search, using specific verb and resource. It distinguishes itself as the 'fetch' entrypoint paired with 'search', differentiating from sibling 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 explicitly mentions it is paired with 'search', indicating usage after search results. However, it does not provide exclusions or alternatives, though the context is 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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