Register an API endpoint to monitor for schema changes. Provide name, url, and optionally method/headers/description.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | API URL to monitor | |
| body | No | Request body (for POST/PUT) | |
| name | Yes | Identifier for this endpoint | |
| method | No | HTTP method (default: GET) | |
| headers | No | Request headers | |
| description | No | Optional description |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry behavioral disclosure. It only states the registration action and monitoring purpose, omitting side effects, idempotency, authentication needs, duplicate handling, or response details. This is minimal transparency.
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 15-word sentence, front-loaded with the core purpose and followed by compact parameter guidance. There is no filler or redundancy.
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?
With 6 parameters, nested headers, and no annotations or output schema, the description leaves significant gaps. It does not explain what happens after registration, whether duplicates are handled, or what the tool returns.
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%, meeting the baseline. The description highlights name, url, method, headers, and description but omits the 'body' parameter, adding little semantic value beyond what the schema already provides.
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 and resource ('Register an API endpoint') and clarifies the purpose ('to monitor for schema changes'). This clearly distinguishes it from sibling tools like compare_snapshots or delete_endpoint.
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 you want to add an endpoint to monitoring) but provides no explicit when-to-use guidance or alternative comparisons. It offers parameter invocation hints ('Provide name, url, and optionally...') rather than context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: CRUD operations for endpoints (register, list, delete) are separate from diff analysis (compare_snapshots, detect_breaking_changes, get_diff_history). Even the two diff-related tools differ in focus: compare_snapshots detects any changes, while detect_breaking_changes specifically flags breaking changes.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., register_endpoint, list_monitored_endpoints, detect_breaking_changes). Verbs are specific and the pattern is predictable throughout.
Six tools is well-scoped for an API diff monitoring server. Each tool covers a distinct aspect of the domain without redundancy, and the count is within the ideal range for coherence.
The tool set covers the core lifecycle of endpoints (register, list, delete) and the primary diff operations (compare, detect breaking, view history). Minor gaps like updating an endpoint or manually triggering a snapshot exist, but the inline comparison option in compare_snapshots provides a workaround for testing changes.