Analyzes breaking changes between two schema versions. Detects: field removal, type changes, newly required fields, enum value removal, constraint tightening.
| Name | Required | Description | Default |
|---|---|---|---|
| newSchema | Yes | New (candidate) schema version | |
| oldSchema | Yes | Previous (deployed) schema version |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Analyzes' implies a read-only operation, the description does not explicitly state non-mutating behavior, nor does it disclose any edge cases, error conditions, or output format. The list of detections clarifies scope but adds little about actual tool behavior beyond the core purpose.
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 sentence with a colon-separated list of detection types. It is front-loaded with the primary purpose and every word contributes to understanding. No redundancy or filler.
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 tool has two parameters and no output schema, and the description lists detection types but does not specify the return format (e.g., a list of breaking changes). It also lacks alternative usage guidance. For a moderately complex analysis tool, the description is adequate but leaves gaps around expected output and edge-case behavior.
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?
The input schema covers 100% of parameters with descriptions ('New (candidate) schema version' and 'Previous (deployed) schema version'). The tool description's mention of 'between two schema versions' aligns with the schema but does not add additional semantic richness beyond what the parameter descriptions already provide. Baseline 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 clearly states the tool 'Analyzes breaking changes between two schema versions' and lists specific change types it detects (field removal, type changes, newly required fields, etc.). This is a specific verb+resource combination. However, it does not explicitly distinguish itself from sibling tools like drift-detector or schema-validator, relying on the tool name for differentiation.
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 implies usage when checking schema compatibility by naming the two inputs 'oldSchema' and 'newSchema'. However, it provides no explicit guidance on when to use this tool versus the sibling tools, nor does it state any exclusions or prerequisites. The context is clear enough to infer basic usage, but it lacks direct comparison to alternatives.
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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Each tool targets a distinct aspect: schema version comparison, actual vs expected response checking, and general data validation. No overlap in purpose.
All tool names follow a consistent pattern: [domain concept]-[tool type] (e.g., breaking-change-analyzer, drift-detector, schema-validator), all lowercase with hyphens.
Three tools is appropriate for the focused domain of schema drift detection, covering the main operations without being too few or excessive.
The tool set covers schema version comparison, API response drift detection, and schema validation, providing a complete workflow for drift detection without obvious gaps.