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trident

by io.github.alexeibespalov
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get_recent_changes

Read-only

Returns the recent change history for a live Trident document. Each entry shows who made the change, what was changed, and when. Useful for understanding what edits have been made by AI agents or human collaborators. Requires a valid access token.

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": {
      "token": "<token>"
    },
    "name": "get_recent_changes"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoOptional: Maximum number of entries to return (default 100, max 500)
sinceNoOptional: Unix timestamp in milliseconds — only return changes after this time
tokenYesAccess token for this document. The document ID is embedded in the token.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds extra behavioral context: the document must be 'live', each entry includes authorship and timestamp, and a valid access token is required. This goes beyond the annotations without contradicting them.

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 three sentences, each serving a distinct purpose: stating the action, describing the value, and noting the requirement. There is no redundancy or unnecessary detail, and the most important information is front-loaded.

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?

The tool is a read-only history query with a well-documented schema and clear return content described at a high level. There is no output schema, but the description indicates what each entry contains. It lacks details on pagination/error handling, but for this simple tool with good annotations, the description is sufficiently complete.

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%, so the schema fully documents all three parameters. The description does not add detail beyond the schema, such as format constraints or examples. It mentions the token requirement but that is already in the schema. 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 uses a specific verb ('Returns') and resource ('recent change history for a live Trident document'), clearly distinguishing it from sibling tools like get_document_summary and get_document_png. It also specifies the content of each entry (who, what, when), leaving no ambiguity about the tool's function.

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 provides clear context: it is useful for understanding edits made by AI agents or human collaborators. While it does not explicitly state exclusions or alternatives, the intended use case is evident, and the sibling list offers related tools for comparison.

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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