ident-mcp

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

Discloses return of expected check digit on failure, but does not describe success behavior (e.g., boolean return). Without annotations, the description could provide more safety or state info.

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?

Single efficient sentence that is front-loaded and contains no unnecessary words. Every part is meaningful.

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 main purpose and failure return. Given simplicity, it is mostly complete, but missing success return and input format notes would enhance 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?

Schema coverage is 100% with a clear description of the parameter. The tool description adds no further semantic meaning beyond the schema, achieving the baseline.

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?

Specifically states validation of barcode check digit for four types (EAN-8, UPC-A, EAN-13, GTIN-14) and return behavior on failure. Clearly distinguishes from sibling validators that handle other identifier formats.

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?

Implied usage—use for barcode validation; sibling tools are for different identifiers. No explicit when-to-use or when-not-to-use guidance, but the context is sufficient for this simple 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?

No annotations provided, so description carries full burden. It clearly discloses the validation steps (mod-97 checksum, country code, length) and the return format (normalized and print-formatted IBAN). The warning about LLM-generated IBANs adds behavioral insight.

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?

Two sentences with no redundant information. Every word serves a purpose, and the key points are front-loaded.

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 validation tool without output schema, the description covers the validation logic, return format, and a practical warning (LLM-generated IBANs). This is sufficient for correct selection and invocation.

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% with a single parameter 'iban' described as 'IBAN, spaces allowed.' The description adds no additional meaning beyond the schema; 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 validates an IBAN with specific checks (mod-97, country code, length) and mentions returning normalized and print-formatted IBAN. It distinguishes from sibling validation tools by specifying the IBAN format.

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 use when validating an IBAN and warns that LLM-generated IBANs usually fail, guiding expectations. However, it does not explicitly state when not to use or name alternatives beyond sibling tool names.

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 provided, so description carries full burden. It discloses check digit validation, ISBN-13 conversion for valid ISBN-10, and allowance of hyphens/spaces, but does not specify return format or behavior on invalid input.

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?

Two concise sentences that front-load the main purpose and add necessary detail without waste.

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?

Lacks description of return value (e.g., boolean or object). No output schema, so description should specify what the tool returns. Incomplete for a validation 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 for 'isbn' is 'ISBN-10 or ISBN-13.' The tool description adds that hyphens and spaces are allowed and mentions the ISBN-13 conversion, providing meaningful context beyond the schema. Schema coverage is 100%, baseline 3, description adds 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?

Clearly states the tool validates ISBN-10 or ISBN-13 check digits and distinguishes it from sibling validators like validate_ean, validate_iban, etc. The description includes specific resource (ISBN) and verb (validate).

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?

Implied usage for ISBN validation, but no explicit guidance on when to use vs alternatives or when not to use. Sibling tools exist but no differentiation notes.

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 mentions validation and timestamp decoding but does not disclose error behavior, return type, or any side effects. For example, it's unclear what happens for invalid input.

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 sentences, front-loaded with the core purpose, and contains no superfluous words. Every sentence 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?

For a simple validation tool with one parameter and no output schema, the description covers the action and output sufficiently. However, it lacks detail on the return format or indicators of validation success/failure, which would be useful for complete contextual understanding.

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% with a basic description. The tool description adds context by specifying the expected format ('26-char Crockford base32') and the decoded output, which enriches the parameter meaning 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 specifies the verb 'validate', the resource 'ULID', and adds the unique feature 'decode its embedded timestamp to ISO 8601'. It clearly differentiates from sibling tools like validate_uuid or validate_isbn.

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?

No explicit guidance on when to use this tool versus alternatives. The purpose is implied by the name and description, but there is no mention of prerequisites, limitations, or comparison to other validation tools.

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 carries full burden. It discloses that the tool catches malformed UUIDs and provides version/variant information, adding behavioral insight beyond the schema.

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?

Two sentences front-load the action and purpose, with no unnecessary words. Every sentence contributes to understanding the tool.

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 simple validation tool with full schema coverage and no output schema, the description is mostly complete. It explains the output's key parts (version/variant) but could explicitly mention return format.

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% for the single parameter. The description adds context about output (version/variant) but does not further clarify the input parameter beyond what the schema 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 clearly states the action (validate), the resource (UUID), and adds details about reporting version and variant, distinguishing it from sibling tools for other identifiers.

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 UUID validation but does not explicitly state when to use this tool over alternatives like validate_ulid. There is no exclusion criteria.

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