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

A dedicated 'Behavioral Transparency' section details side effects (read-only), authentication, rate limits, error handling, idempotency, and data privacy, fully compensating for the absence of annotations.

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 well-structured with clear sections but is verbose and contains redundant information between 'Behavior' and 'Behavioral Transparency' sections. Could be more concise.

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 no output schema, the description covers input parameters, behavior, errors, and limitations well. However, it lacks explicit description of the return structure beyond mentioning 'structured output' and error objects, which is a minor gap.

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 'Args' section provides brief descriptions that largely restate parameter names. However, the description adds value by listing example pattern types for 'pattern_type', but does not fully compensate for 0% schema coverage, especially for 'custom_options' which lacks format constraints.

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 builds common regex patterns and lists specific types, including custom patterns. It distinguishes from siblings like explain_regex, extract_matches, and test_regex by focusing on pattern construction.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance on appropriate contexts and limitations, such as not for real-time production decisions without human review.

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?

Extremely detailed behavioral disclosure covering read-only nature, idempotency, rate limits, authentication, error handling, and data privacy. Since no annotations are provided, this description fully compensates and provides comprehensive 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 well-structured with clear sections and front-loads the primary purpose. However, there is redundancy between the general behavior section and the detailed behavioral transparency section, making it slightly longer than necessary.

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?

Covers purpose, behavior, usage, limitations, and privacy well. The presence of an output schema means return value details are not needed. However, parameter descriptions are insufficient, and the inconsistency about api_key authentication reduces completeness.

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 'Args' section provides minimal descriptions ('The pattern to analyze or process') that do little beyond restating parameter names. There is inconsistency between the api_key parameter description and the later mention of environment variable MEOK_API_KEY. With 0% schema description coverage, the description fails to sufficiently clarify parameter meaning.

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 purpose in the first sentence: 'Explain a regex pattern in plain English.' It distinguishes from siblings (build_regex, extract_matches, test_regex) by focusing on explanation rather than building, extracting, or testing.

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?

Provides dedicated 'When to use' and 'When NOT to use' sections, offering clear guidance on appropriate contexts. While it does not explicitly compare to sibling tools, the usage guidance is sufficient for a user to understand when to choose this tool.

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 provided, the description carries full burden and excels. It includes a dedicated 'Behavioral Transparency' section covering side effects (read-only, stateless), authentication (none for basic, API key for pro), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency (fully idempotent), and data privacy (no storage/logging).

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 well-structured with clear sections (behavior, when to use, args, behavioral transparency). It is front-loaded with the core purpose. The behavioral section is detailed but valuable; every sentence contributes useful information, though it could be slightly more concise.

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 presence of an output schema (which covers return values), the description provides thorough behavioral context (rate limits, errors, idempotency). It lacks deep parameter explanations but compensates with group clarification. Overall, sufficiently complete for a regex extraction tool.

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 0%. The 'Args' section merely lists parameter names with the generic phrase 'to analyze or process,' adding no meaning beyond the schema. However, the initial description clarifies the group parameter's meaning (0 for full, 1+ for captures). No explanation is given for pattern (e.g., regex) or text content.

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 extracts matches of a pattern from text, with specific explanation of the group parameter (0 for full match, 1+ for capture groups). It distinguishes itself from sibling tools (build_regex, explain_regex, test_regex) which serve different purposes.

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 'When to use' section provides generic guidance about structured analysis/classification, but does not specifically relate to pattern extraction or compare with sibling tools. The 'When NOT to use' mentions not for real-time decision-making without human review, which is vague. No explicit alternatives are named.

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 carries the burden. It comprehensively covers side effects (read-only), authentication (none for basic), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency, and data privacy. All claims are specific and actionable.

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 well-structured with headings, but it is verbose and contains redundancy (e.g., 'Behavioral Transparency' section largely repeats earlier lines about read-only, authentication, and rate limits). The first sentence effectively captures the core purpose.

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?

While the description covers behavior, auth, and errors well, it fails to mention the tool's output format beyond error objects. An output schema exists but the description does not indicate what a successful response contains (e.g., match results, indices). This leaves ambiguity about the return value.

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?

Input schema has 0% description coverage, so the description must compensate. However, the 'Args' section merely restates parameter names and adds the generic phrase 'to analyze or process' for each, without explaining valid values, formats, or the role of 'api_key'. This adds minimal semantic value.

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 a regex pattern against a string, including flag options. It distinguishes from sibling tools (build_regex, explain_regex, extract_matches) by focusing on testing functionality.

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 'When to use' and 'When NOT to use' sections, but the guidance is generic (e.g., 'structured analysis or classification of inputs') and not specific to regex testing. It lacks explicit comparison to sibling tools for when to choose testing over building or extracting.

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