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api-contract-validator

check_breaking_changes

Compare two OpenAPI spec versions to detect breaking changes: removed paths/operations, new required parameters, removed response codes, operationId renames.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spec_newYesNew spec version
spec_oldYesPrevious spec version

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses what the tool detects (breaking change categories), adding useful behavioral context. However, it does not describe the return format, whether it is read-only, or any side effects. The added detail is helpful but not comprehensive.

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 a single, front-loaded sentence that lists the key detection categories without extraneous words. It is concise and well-structured, earning full marks.

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?

The tool has two nested object parameters and no output schema, so the description must cover both purpose and expected results. It explains the purpose and lists detection categories but omits the return format and any prerequisites. Adequate but not complete for a tool with this complexity.

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 baseline is 3. The schema already defines spec_old as 'Previous spec version' and spec_new as 'New spec version'. The description adds the context of comparing them but does not add per-parameter semantics beyond the schema.

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 the tool's function with a specific verb and resource: 'Compare two OpenAPI spec versions to detect breaking changes'. It further enumerates concrete examples (removed paths/operations, new required parameters, removed response codes, operationId renames), which distinguishes it from sibling tools like diff_request_response or lint_api_schema.

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 for detecting breaking changes when comparing two spec versions. It does not explicitly state when not to use it or mention alternatives, but the use case is evident from the description. This merits a 4 rather than a 5.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool serves a distinct purpose: validation, linting, breaking change detection, request/response diffing, and mock generation. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (check_, diff_, generate_, lint_, validate_), making the naming predictable and easy to navigate.

Tool Count5/5

With 5 tools, the set is well-scoped for an API contract validator. Each tool covers a distinct aspect of specification validation and testing without excess or redundancy.

Completeness5/5

The toolset comprehensively covers the core domain: structural validation, linting, breaking change detection, runtime request/response validation, and mock generation. No obvious gaps remain for typical contract-validation workflows.