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

No annotations are provided, so the description carries the burden. It specifies the HTTP method (GET), response codes (200, 400, 500), and implies read-only behavior. It could mention idempotency or lack of side effects, but it is still fairly transparent.

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 structured with endpoint, method, description, parameters, responses, and an example. It is informative but slightly verbose; could be more concise, but still well-organized.

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 tool with one parameter and no output schema, the description is complete. It covers input validation, response shapes (200 returns address, errors), and provides an example. No additional context needed.

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 description adds meaning beyond the schema: it states the requirement for a 15-character valid GST number, while the schema only provides an example. This helps the agent understand validation 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 'Retrieves the address associated with the provided GST number', which is a specific verb+resource combination. It is distinct from sibling tools like get_gst_details_using_gst_number which likely returns other details.

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 provide guidance on when to use this tool versus alternatives such as get_gst_details_using_gst_number. There is no explicit 'when to use' or 'when not to use' context.

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 present, so the description carries the burden. It discloses that the HTTP method is GET (implying read-only) and lists possible response codes (200, 400, 500) with an example. However, it does not explicitly state that the operation is non-destructive or mention authentication or rate limits.

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 sections for endpoint, method, parameters, responses, and example. Each sentence is relevant, though it could be more concise by omitting the full endpoint path which duplicates the tool name.

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?

With no output schema, the description only vaguely mentions 'Returns GST details along with a timestamp' without specifying the actual fields or format. The parameter name discrepancy undermines completeness, and error responses are listed but not detailed for each code.

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?

While the description adds a human-readable explanation ('The name of the company') and an example request, it mistakenly uses 'companyName' instead of the schema's required parameter 'name'. This contradiction outweighs the added value, as the agent may send the wrong key.

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 that it fetches GST details using the company name, differentiating it from siblings like get_gst_details_using_gst_number. However, the parameter name mismatch between the description (companyName) and the schema (name) casts doubt on whether the agent will invoke it correctly, slightly reducing clarity.

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 usage guidelines provided; the description does not specify when to use this tool over siblings or mention any prerequisites. Worse, it gives an incorrect parameter name (companyName instead of the schema's name), which is misleading and could cause invocation failures.

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 the read-only nature (GET method), parameter format (15-character), and error responses (400, 500). However, lacks details on authentication or rate limits, but acceptable for a simple lookup.

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 paragraph with technical details (endpoint, method, responses) but is somewhat verbose and not tightly structured. Could be more concise while retaining all key information.

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 GET request with one parameter and no output schema, the description adequately covers purpose, input, and expected responses (200, 400, 500). Missing detailed response structure, but overall 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 input schema only provides an example value with 100% coverage. The description adds meaningful context: 'A valid GST number (15 characters)' and an example request, clarifying the required format 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 it fetches GST details using a GST number. The sibling tools (e.g., get_gst_details_using_company_name, get_gst_details_using_pan) differ in input, making this tool distinct and specific.

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?

Explicitly specifies the HTTP method, endpoint, required parameter, and response codes. Implicitly suggests usage when a GST number is available, but lacks explicit guidance on when not to use or alternatives.

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 HTTP responses (200, 400, 500) and mentions a timestamp, but does not address read-only nature, permissions, rate limits, or side effects.

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 includes redundant sections (e.g., repeating endpoint and method) and is longer than necessary. However, it is organized clearly with segmented info. Some sentences could be streamlined.

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 1-param tool without output schema, the description covers core aspects: purpose, input, responses, and an example. However, it lacks a breakdown of the return data fields, which 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?

The schema has 100% coverage with a description example. The description adds format and length details (e.g., 'valid PAN number (10 characters)') that supplement the schema, providing clear parameter semantics.

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 fetches GST details using a PAN number. It specifies the resource (GST details) and the input key (PAN number), distinguishing it from siblings that use GST number or company name.

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 PAN-based queries but does not explicitly state when to prefer this over alternatives or when not to use it. No exclusions or context are provided.

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?

Annotations are absent, so the description carries the full burden. It discloses the HTTP method (GET) and possible response codes (200, 400, 500), but it does not address rate limits, authentication, or confirm read-only behavior beyond the verb 'Fetches.'

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 overly verbose, including endpoint, method, and full response details, some of which may be redundant for an MCP tool. It is structured but could be more concise by focusing on the purpose and parameter details.

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 and no annotations, the description provides a good level of completeness: it explains input, expected output (filing status with timestamp), and error responses, plus an example. However, the parameter name mismatch and lack of year differentiation slightly reduce clarity.

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 provides an example value but lacks a description of the parameter's meaning. The description compensates by stating 'A valid GST number (15 characters),' adding clarity beyond the schema. However, there is a mismatch: the description uses 'gst' while the schema uses 'GSTNumber', which could cause confusion.

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 'Fetches the GST return filing status of the provided GST number,' which is a specific verb and resource. It distinguishes from siblings like 'get_gst_return_filing_status_for_a_specific_year' by not including a year parameter.

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. While the description provides context, it does not mention when not to use it or compare with siblings such as 'get_gst_status' or 'get_gst_details_using_gst_number'.

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; description only mentions HTTP method and response codes. Missing details on whether it's read-only, permissions required, rate limits, or error handling beyond 400/500.

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?

Concise single paragraph with front-loaded purpose. Includes endpoint, method, parameter list, and response codes. Ends abruptly but overall 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?

With no output schema, response description is brief but mentions status and timestamp. Missing details on error formats, status values, or pagination. Adequate for a simple fetch 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 coverage is 100%; description adds context beyond schema by specifying GST number must be 15 characters and providing endpoint path. Year description is minimal but matches schema example.

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?

Explicitly states it fetches GST return filing status for a specific year using GST number and year. Clearly distinguishes from generic sibling 'get_gst_return_filing_status' by specifying 'for a specific year'.

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?

Implies usage when a specific year is needed, but no explicit guidance on when to use this versus the generic sibling or alternatives. No exclusions mentioned.

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 for behavioral disclosure. It mentions HTTP method and responses but fails to state that the operation is read-only, idempotent, or any rate limits or authentication requirements. The value 'status' is not elaborated.

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 verbose, including raw endpoint, method, and response codes that could be condensed. It is front-loaded with the purpose but contains redundant elements like the full example curl path.

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 one-parameter retrieval tool with no output schema, the description is fairly complete: it specifies required parameter, format, example, and possible responses. However, it lacks explanation of what the returned 'status' and 'timestamp' represent.

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. The description adds value by specifying the expected format (15 characters, valid GST number) and provides an example, which goes beyond the schema's minimal description.

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 states 'Retrieves the status of the provided GST number,' which is a clear verb+resource combination. However, it does not distinguish 'status' from 'details' or 'validation' as offered by sibling tools like get_gst_details_using_gst_number and validate_gst_number, causing potential confusion.

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 guidance is provided on when to use this tool versus alternatives. The description lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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. The description mentions the GET method (implying read-only) and lists response codes (200, 400, 500) with brief meanings, but does not disclose side effects, authentication needs, or rate limits. Adequate but minimal behavioral context.

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 sections for endpoint, method, parameters, and responses. It is somewhat lengthy due to the example, but the key purpose is front-loaded. Slightly verbose but effective.

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?

With no output schema, the description adequately explains return types (validation results with timestamp) and error responses. For a single-parameter tool, it provides sufficient context, though the response structure could be more detailed.

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 one parameter. The description adds meaning by specifying the required length (15 characters) and providing an example usage in the endpoint, though there is a mismatch between the description parameter name 'gst' and schema property 'GSTNumber'.

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 it validates a GST number, with specific verb and resource. It distinguishes from sibling tools (e.g., get_gst_details_using_gst_number) by focusing on validation rather than retrieval of details.

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 guidance on when to use this tool versus siblings. For example, it does not say to use this for validation only and other tools for detailed information. The description is purely technical.

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