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

No annotations provided, so description carries full burden. It implies a read-only retrieval operation (조회합니다). It adds context about special id=0 behavior but does not disclose other traits such as error handling, rate limits, or output format. Adequate but not thorough.

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 concise (3 sentences), front-loaded with the main purpose, and structured with a clear usage scenario. No unnecessary words.

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 single-parameter retrieval tool, the description covers the main purpose, usage context, and a key special case. It references sibling tool get-docs for search. Lacks details about output format but is sufficient given no output schema.

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 description adds value by explaining the special meaning of id=0 (list all IDs), which is not in the schema. This enhances parameter understanding.

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 retrieves entire documentation for a specific integration by ID, and distinguishes from sibling tool get-docs by specifying that get-docs is for search results while this tool gets full content. It also explains the special id=0 behavior for listing IDs.

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 explicitly tells when to use: when full content from get-docs search results is needed. It also provides usage guidance for id=0 to list IDs. However, it does not explicitly state when not to use it or list alternatives beyond get-docs.

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 should disclose behavioral traits. It only lists documents and security rules, but does not mention read-only nature, side effects, rate limits, or return format. The tool's output behavior is completely unclear.

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, mixing tool purpose, a long list of document types, and extensive security rules that are not directly relevant to the tool's operation. The structure is front-loaded with purpose, but the second half is overly detailed and could be trimmed.

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 description provides a comprehensive list of available documents and security rules, which is useful for context. However, it lacks information about return format, pagination, or error handling. Without an output schema, the description should cover these gaps more fully.

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 fully describes the single parameter (keywords) with a clear example. The description adds no additional meaning beyond the schema, so baseline of 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 searches for KG파이낸셜 payment integration documents, specifying two systems and listing supported document types. However, it does not differentiate from sibling tools like document-by-id or get-nezo-api-spec, which limits clarity for selection.

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 includes security rules for coding, but does not help an agent decide between this tool and other document tools on the same server.

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 adds meaningful behavioral context: security rules (client-side avoidance of keys, server-side HMAC, idempotency, environment separation). It implies the tool is read-only and returns full documentation, but doesn't detail output format 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 is reasonably concise and well-structured: purpose sentence, usage context, list of api_names, then security rules. Some redundancy exists (e.g., security rules could be separate), but overall it's clear and 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?

Given no output schema, the description should mention the format of the returned spec (e.g., JSON). It covers purpose, parameters, and security, but lacks details on authentication prerequisites and return structure, leaving some gaps.

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 already covers the api_name parameter well (100% coverage). The description adds value by listing all valid values with translations and notes, going beyond the schema's examples.

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 the tool retrieves the full specification of the NEZO Alimtalk payment service API for a specific api_name, distinguishing it from sibling tools like get-nezo-code-example. It lists all possible api_name values, making the purpose very 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?

The description tells when to use this tool (exact API spec lookup, not keyword search) and provides context for choosing api_name. However, it does not explicitly compare with sibling tools or state when not to use it, missing some guidance.

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 mentions returning code blocks filtered by language and includes security rules (e.g., do not embed keys in client code). However, it does not disclose error behavior, whether multiple matches are returned, or the exact output structure.

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 about five sentences, front-loaded with the main purpose, and clearly written. The security rules are relevant but slightly extend the length; still efficient for the information conveyed.

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 lookup tool with no output schema, the description explains the purpose, parameters, and security considerations. However, it does not describe the return format or behavior when no matching examples exist, leaving moderate gaps.

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% and both parameters have descriptions. The description adds value by listing the available languages (Java, C#, Node.js, Python, PHP) and mentioning the MAC guide document, which helps clarify valid values and context 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 looks up language-specific example code for NEZO notification payment service, with a verb and resource. It distinguishes from siblings by specifying 'NEZO' scope, but does not explicitly differentiate from get-payment-code-example.

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 alternatives like get-payment-code-example or get-docs. The description lacks any '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 provided; description carries the burden. It discloses security-sensitive rules (e.g., skey, HMAC) but does not mention read-only nature, error handling, or response format. Adequate but not comprehensive.

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?

Well-organized into three sections (purpose, API list, security rules). A bit verbose but not excessive. Each section serves a clear 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?

For a single-parameter tool with no output schema, the description is thorough: explains what it returns, lists valid inputs, and provides essential security context. No gaps.

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 significant value by listing all valid api_name values explicitly, beyond the schema's examples, thus compensating fully.

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 it retrieves the full specification of the MOBILPAY REST API, including parameters and example code. Explicitly distinguishes from keyword search or fuzzy lookup by specifying '키워드 검색이 아닌 특정 API를 정확히 조회할 때 사용합니다.'

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 usage context (exact API lookup) and security rules (skey, HMAC, approval API). However, it does not explicitly compare with sibling tools like get-nezo-api-spec or get-docs, leaving some ambiguity.

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 the description carries full burden. It explains the tool returns filtered code blocks and adds security context but does not explicitly state it is read-only or non-destructive.

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 concise, well-structured, and front-loaded with the purpose, followed by filtering explanation and important security rules.

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 retrieval tool with no output schema, the description covers the essential behavior and security considerations, though it omits the exact output 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% with descriptions for both parameters. The description adds some context (listing example languages from HMAC doc), but does not significantly enhance understanding 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 retrieves language-specific example code for MOBILPAY REST API, distinguishing it from siblings like get-nezo-code-example which target a different API.

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 important security rules for using the code (e.g., server-side processing), but does not explicitly guide when to use this tool vs alternatives or when not to use it.

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