Query refined developer changelogs, API deprecations, breaking changes, and migration code diffs for packages/APIs.
| Name | Required | Description | Default |
|---|---|---|---|
| breakingOnly | No | If true, only returns breaking change entries | |
| targetVersion | No | Target version or version range (optional) | |
| packageOrService | Yes | Name of package or API (e.g., 'stripe-node', 'nextjs', 'openai') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral disclosure burden. 'Query' implies a read-only operation, and the listed content types are helpful. However, it does not disclose response format, pagination, version-range handling, or any caveats about the returned data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. Every clause contributes useful information about the tool's scope and content types.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is insufficiently complete for an agent selecting among many refinery tools. It fails to disambiguate from refinery_custom_dev_sdk_breaking_changes, offers no usage context, and provides no indication of what the response looks like despite there being no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and each parameter already has a clear description in the input schema. The tool description adds little semantic value beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Query') and names the resource clearly: refined developer changelogs, API deprecations, breaking changes, and migration code diffs for packages/APIs. It is easy to understand what the tool does, but it does not explicitly differentiate itself from the similarly named sibling tool refinery_custom_dev_sdk_breaking_changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance about when to use this tool instead of alternative refinery tools. A near-identical sibling name exists, yet there is no mention of which scenarios favor this tool or when the sibling should be selected instead.
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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Several tools form near-overlapping pairs: b2b_pricing_matrix vs custom_b2b_saas_pricing_matrix, dev_breaking_changes vs custom_dev_sdk_breaking_changes, and municipal/real-estate zoning vs regulatory_compliance. While individual descriptions differ, an agent would often have to guess which variant applies.
Names share a refinery_ prefix and use snake_case, making them mostly predictable and readable. The custom_ qualifier is used inconsistently—custom schema vs custom URL—and refinery_refine_custom_url/semantic_search break the otherwise noun-object pattern, but these are minor deviations.
13 tools is reasonable for a data-refinery platform covering multiple vertical schemas. The redundancy between base and custom_ variants and overlapping compliance tools makes it slightly heavier than necessary, but not excessive.
The surface covers refining arbitrary URLs, semantic search, and many domain-specific extraction schemas. Missing are database/schema management, document-level retrieval/update/delete, and clear parity between base and custom variants, so agents may hit dead ends when managing or verifying refined data.