Regex/Email/URL Validator

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

With no annotations provided, the description carries full burden to disclose behavioral traits. It thoroughly covers key behaviors: syntax-only validation, acceptance of addresses without TLD, and rejection of display-name syntax. No contradictions are present.

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 extremely concise at two sentences. The first sentence front-loads the core purpose and scope. Every word serves a purpose, with no fluff 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?

Given it is a simple single-parameter tool with full schema description, an explicit output schema, and straightforward purpose, the description is complete. It clarifies the validation algorithm (RFC 5322, syntax only) and key boundary cases, leaving no ambiguity for an AI agent.

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% (the single parameter 'value' is described as 'identifier or value to check'). The description adds important context about the expected format (bare RFC 5322 email, not a display name), which helps the agent understand what input to provide. However, it does not elaborate on edge cases like whitespace handling or case sensitivity, which could further enhance understanding. 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 checks if a value is a single, bare RFC 5322 email address. It specifies the scope is syntax-only, not deliverability, which helps distinguish from other validation tools. The examples of valid ('user@localhost') and invalid ('Name <email>') cases further clarify the exact boundary.

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 implicitly guides when to use this tool via the 'syntax only, not a deliverability check' clause, suggesting it is for format validation, not for verifying an email exists. It does not explicitly state when not to use it or compare to siblings, but the context of siblings (jsonschema_validate, regex_match, url_validate) and the clear scope make misuse unlikely without further elaboration.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description fully bears the burden of behavioral disclosure. It discloses that the tool returns one violation per call, which is a key behavioral trait. However, it does not state whether the operation is read-only, has side effects, or requires authentication. Since validation is typically side-effect-free, the lack of explicit mention is a minor gap. With an output schema present, return format details are not required, but the description could be more transparent about the nature of the operation.

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 consists of two concise sentences. The first sentence establishes the core purpose, and the second adds a critical behavioral detail. Every word is purposeful; there is no redundancy or fluff. The structure is front-loaded and efficient.

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?

Given the tool's simplicity (2 parameters, output schema exists), the description is largely complete. It covers the purpose and a key behavioral trait (one violation per call). The output schema likely handles return value details. The description could mention that the tool is read-only or that it expects a well-formed schema, but these are reasonable assumptions. Overall, it provides sufficient context for appropriate use.

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 both parameters with descriptions, achieving 100% coverage. The description adds little beyond the schema: 'a JSON Schema (draft-07 or 2020-12)' for 'schema' and 'the JSON value to validate against schema' for 'document' are clear but not significantly enriched. Baseline 3 is appropriate as the schema already does the heavy lifting.

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 'Validates document against schema (JSON Schema draft-07 or 2020-12).' This specifies the verb (validates), resource (document against schema), and scope (specific schema versions). The tool is distinct from siblings like email_validate, regex_match, and url_validate, which are format-specific validators. The additional behavioral note about reporting one violation per call further refines the purpose.

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 does not explicitly state when to use this tool versus alternatives. It provides a behavioral nuance ('Reports one specific violation per call, not an aggregated list'), which implies that for complete validation, multiple calls may be needed. However, it does not mention that for format-specific validation (e.g., email, regex, URL), sibling tools should be used. The usage context is implied but not explicitly contrasted.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description transparently discloses the RE2 syntax constraints (no backreferences/lookaround) and the return behavior (full match and captured groups). It does not mention edge cases like no-match behavior, but covers key aspects.

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 well-structured sentence that front-loads the purpose and adds parenthetical syntax details without waste. Every word adds value.

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?

Given the tool's simplicity, the description covers the purpose, parameter roles, syntax rules, and return value. The existence of an output schema means return-value details don't need full explanation, so this is sufficient.

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 only describes 'pattern' as 'RE2 syntax', leaving 'input' undocumented. The description clarifies both: input is the string to test, pattern is the regex, and adds detail about RE2 limitations and flags beyond the schema.

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 tests input against a pattern and returns the full match and captured groups. It distinguishes itself from sibling validators (email_validate, url_validate, jsonschema_validate) by being the general regex matching tool.

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 for regex matching, with context about Go's RE2 syntax and inline flags. It does not explicitly say when not to use it or compare with alternatives, but the regex-specific details make the use case clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.