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Adaga solutions — Data APIs Toolbox

api_breaking_change_radar

Monitor public APIs and detect breaking changes by diffing OpenAPI specs and classifying changelogs — a radar for the APIs you depend on. Use when you need early warning before an API change breaks your integration. Returns change events classified by severity. Pricing: $0.50 per run + $0.005 per API checked.

Input Schema

NameRequiredDescriptionDefault
apisYesList of APIs to watch. For type 'openapi', url must point to a raw OpenAPI spec (JSON or YAML). For type 'github-releases', url must be 'owner/repo' or a GitHub repo URL. For type 'rss', url must be an RSS/Atom changelog feed.
dryRunNoWhen true, the actor performs the full detection but does NOT charge any pay-per-event fee. Use for testing your configuration.
maxApisNoSafety cap on the number of APIs processed in one run.
webhookUrlNoPOST endpoint called at the end of each run with a JSON summary (counts by class + top critical changes). Slack/Discord/Teams incoming-webhook compatible payload is included.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does meaningful work: it discloses the pricing model ($0.50/run + $0.005/API), the return shape (change events classified by severity), and the underlying mechanisms (oasdiff diffing vs rule-based classification). It does not explicitly state read-only/safety characteristics, but the monitoring framing makes mutation risk clear.

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?

Four compact sentences that front-load the purpose before moving to usage, return, and cost. The 'radar for the APIs you depend on' phrase is mild flavor but earns its place as shorthand; nothing is wasted overall.

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?

No output schema exists, so the description usefully summarizes the return as severity-classified change events, and it discloses pricing, which annotations do not cover. For a 4-parameter monitoring tool with full schema coverage, this is nearly 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 all four parameters (apis, dryRun, maxApis, webhookUrl) are already fully documented in the schema. The description adds no syntax or format detail beyond what the schema provides, so the baseline of 3 applies.

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?

States a specific verb and resource: monitors public APIs and detects breaking changes by diffing OpenAPI specs and classifying changelogs. Clearly distinguishable from all siblings, which are unrelated scrapers and checkers.

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?

Explicitly names the triggering condition: 'Use when you need early warning before an API change breaks your integration.' Sibling tools are unrelated, so no alternative routing is needed, but it offers no when-not to run guidance (e.g. no-change cost considerations).

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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