api_discoveryDiscover OpenAPI, Swagger, GraphQL, MCP, and API documentation signals. Price: $0.10 USDC. Example: GET /v1/api-discovery?url=https://example.com
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds the cost ($0.10 USDC) and an example HTTP GET pattern, which are useful, but it does not disclose output format, error behavior, authentication needs, or rate limits. 'Signals' gives a vague hint of return content.
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 two concise sentences: the main purpose is front-loaded, followed by cost and an example. Every word adds value, with no filler or repetition.
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?
For a single-parameter discovery tool with no output schema, the description covers purpose and invocation (via example) but lacks details on return structure, edge cases, or usage context relative to similar tools. It is adequate but not comprehensive.
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 schema has one required 'url' parameter with 0% description coverage. The example '?url=https://example.com' partially demonstrates the parameter's meaning, but the description does not explicitly state that the URL is the target to scan. It compensates somewhat but leaves room for ambiguity.
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's function: 'Discover OpenAPI, Swagger, GraphQL, MCP, and API documentation signals.' It uses a specific verb and resource list, and the name 'api_discovery' matches. The focus on discovery distinguishes it from sibling preflight/check tools.
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 through the example 'GET /v1/api-discovery?url=https://example.com' but does not explicitly state when to use this tool vs alternatives like access_check or preflight. There is no mention of alternatives or exclusions, so guidance is only implicit.
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.
Several tools overlap significantly: preflight, premium_preflight, and batch_preflight all perform URL preflight with varying price/features, and access_check appears to be a subset of preflight. This creates ambiguity in selecting the right tool for a task.
Most names use snake_case, but the pattern varies: some end in _check, _preflight, _discovery, or _intel, and preflight is a single word without a verb. The naming is readable but not uniformly consistent.
With 7 tools, the count is well within the ideal 3-15 range and appropriate for a URL preflight service that covers different access levels, batch processing, and specialized checks.
The tool set covers core preflight, access, commerce, API discovery, change detection, and batch operations. Minor gaps exist (e.g., no dedicated raw fetch or history endpoint), but they are not critical and can be worked around.