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query_changelog

Query the Trillboards API changelog for recent changes, breaking changes, deprecations, and fixes.

WHEN TO USE:

  • Check what has changed in the API before upgrading an integration.

  • Find breaking changes since a specific date.

  • Discover new features added to a specific API surface.

PARAMETERS:

  • since (YYYY-MM-DD, optional): Only entries dated on or after this date. Unreleased entries are always included.

  • type (string, optional): Filter by change category. Accepts: "breaking" → changed + removed entries "additive" → added entries "deprecation" → deprecated entries "fix" → fixed entries Can be comma-separated: "breaking,deprecation"

RETURNS:

  • object: "list"

  • data: Array of { version, date, type, surface, description }

  • total: Number of matching entries.

EXAMPLE: Agent: "What broke since April 1st?" query_changelog({ since: "2026-04-01", type: "breaking" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by change category: "breaking", "additive", "deprecation", "fix". Comma-separated for multiple.
sinceNoOnly entries dated on or after this date (YYYY-MM-DD). Unreleased entries are always included.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / since / description
      Added value: +"Only entries dated on or after this date (YYYY-MM-DD). Unreleased entries are always included."
    • addedInput schema / properties / type / description
      Added value: +"Filter by change category: \"breaking\", \"additive\", \"deprecation\", \"fix\". Comma-separated for multiple."
  2. Added

TDQS

A4/5.0
Behavior3/5

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

Without annotations, the description carries the full burden. It discloses the return structure (object with 'list' and 'data' array of objects) and notes that unreleased entries are always included. However, it does not explicitly state that the operation is read-only, address rate limits, or describe ordering/pagination, leaving some behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear headings (WHEN TO USE, PARAMETERS, RETURNS, EXAMPLE) and front-loaded with the purpose. It is somewhat longer than necessary due to repeating schema content, but it remains organized and each section adds value, so it earns a 4.

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 only two parameters and no output schema, the description provides rich context: usage scenarios, parameter explanations, return format, and a concrete example. This is complete for the tool's complexity and makes up for the lack of an output schema.

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 description's PARAMETERS section essentially reiterates the schema descriptions. The example at the end adds practical usage context but does not introduce new parameter semantics beyond what the schema already documents, 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 'Query the Trillboards API changelog for recent changes, breaking changes, deprecations, and fixes,' which precisely identifies the tool's function and resource. It distinguishes from sibling tools like get_analytics or list_error_codes by being specifically about the changelog.

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 'WHEN TO USE' section explicitly provides three concrete scenarios, such as checking changes before upgrading an integration or finding breaking changes since a date. This gives clear context for when to use the tool, though it does not explicitly mention alternatives or exclusions, so a 4 is appropriate.

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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