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Read the edit history of a company knowledge document with GPT change summaries and processing state

summer_knowledge_history
Read-onlyIdempotent

Read the edit history of a company knowledge document with GPT change summaries and processing state. Set actor=summer for Summer plans and Teach Summer edits.

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": {
      "company": "<company>",
      "document": "<document>"
    },
    "name": "summer_knowledge_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
actorNo
offsetNo
companyYesSummer company ID
documentYesKnowledge document ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / actor
      Added value: +{
      +  "enum": [
      +    "all",
      +    "summer"
      +  ],
      +  "type": "string"
      +}
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare the tool is read-only, idempotent, and non-destructive, so the description does not need to restate safety. It adds useful behavioral context by saying the history includes GPT change summaries and processing state, but it does not mention pagination behavior, ordering, limits, or any permission constraints for a history read.

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?

Two short sentences, front-loaded with the purpose and followed by the actor guidance. Every sentence adds useful information and there is no filler.

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

Completeness3/5

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

For a read-only history tool with no output schema and four parameters, the description covers the core purpose and actor filtering. It omits important details such as how offset pagination works, what the processing state values mean, and how the returned history is ordered, leaving gaps an agent may need to resolve.

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 50%. The description clarifies the actor enum values by explaining 'actor=summer for Summer plans and Teach Summer edits,' but it does not explain the offset parameter or add meaning beyond the schema descriptions for company and document. It partially compensates for the coverage gap but leaves offset undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Read the edit history of a company knowledge document,' and adds that it includes GPT change summaries and processing state. It is clear what the tool does, but it does not explicitly distinguish itself from nearby siblings such as summer_knowledge_changes or summer_knowledge_get.

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 only usage guidance is 'Set actor=summer for Summer plans and Teach Summer edits,' which explains how to use one parameter but not when to choose this tool over alternatives. There is no explicit when-to-use, when-not-to-use, or prerequisite 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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