Checks value is a well-formed absolute URL (has both a scheme and a host) — syntax only, not a reachability check.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | identifier or value to check |
| Name | Required | Description | Default |
|---|---|---|---|
| valid | Yes | ||
| reason | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses that the check is syntactic and does not verify reachability, which is a critical behavioral trait. It does not mention side effects (none expected) or error behavior, but given the tool's simple nature and the existence of an output schema, this is sufficient.
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, front-loaded sentence with no extraneous words. It immediately states the action, the resource, and the limitation. Every phrase earns its place.
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 is simple (one parameter), and an output schema exists. The description covers the core behavior and a key limitation. It doesn't detail output format or error scenarios, but these are likely handled by the schema. Some may want a brief note on what the result looks like (e.g., boolean), but overall it's complete enough.
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 coverage is 100%, but the schema description for 'value' is generic ('identifier or value to check'). The tool description adds meaning by specifying that the value should be a URL and what constitutes a valid one. This compensates for the schema's vagueness.
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 explicitly states that the tool checks if a value is a well-formed absolute URL, specifying the criteria (scheme and host). This clearly distinguishes its domain from sibling tools like email_validate or regex_match, though it doesn't name them. The purpose is unambiguous and actionable.
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 includes a key usage note: 'syntax only, not a reachability check,' which clarifies when to use it (syntactic validation) and when not to (live checks). It doesn't explicitly compare to siblings, but the domain difference is self-evident given the tool name and sibling set.
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 targets a distinct validation domain: email, URL, regex, and JSON schema. There is no overlap; an agent can clearly distinguish which tool to use for a given validation task.
All tools follow a consistent verb_noun snake_case pattern (e.g., email_validate, url_validate). The use of 'match' for regex is a minor variation but still fits the pattern, and overall naming is predictable.
Four tools is a well-scoped number for a validation utility server. It covers the main advertised domains without being bloated or too sparse.
The server covers its named areas (regex, email, URL) and adds JSON schema validation. Missing a generic string pattern validator or phone number validator, but the scope is sufficiently covered for common use cases.