venumark

fetch

Alias of get_scorecard for ChatGPT Deep Research connectors. Takes a vendor id from search and returns the full public scorecard as a document (id, title, text, url, metadata).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "fetch"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Vendor id (UUID) from search

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 6, 2026

TDQS

A3.6/5.0

Behavior2/5

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

No annotations are provided, so the description bears the full burden. It describes the tool as an alias for fetching a scorecard and lists return fields, but it does not disclose that the operation is read-only, any authentication requirements, or potential side effects. Given no annotations, this is insufficient.

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 a single, well-structured sentence that front-loads the core purpose (alias of get_scorecard) and includes essential details about input and output. Every phrase earns its place with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one required parameter, no output schema), the description adequately covers the input and output structure. It identifies the tool as an alias and specifies the return fields. However, it lacks information about error conditions, rate limits, or the exact format of the 'document', though these may be inferred. Overall, it is sufficient for a straightforward fetch operation.

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% for the single parameter 'id', which already describes it as a vendor ID (UUID). The description redundantly states 'Takes a vendor id from search', adding no new meaning beyond what the schema provides. Baseline score 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 it is an alias of get_scorecard for ChatGPT Deep Research connectors, specifies the input (vendor id from search), and explicitly lists the output fields (id, title, text, url, metadata). This distinguishes it from sibling tools like get_scorecard by clarifying its specific use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that the vendor id should come from a search, but it does not provide explicit guidance on when to use this tool versus its alias get_scorecard, nor does it mention any alternatives or exclusions. The context is clear but lacks direct instruction.

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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