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

No annotations provided, but description discloses that all $ref references are dereferenced, a key behavioral detail. Could mention output format or auth implications, but overall adequate.

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?

Three concise sentences, front-loaded with purpose, no wasted 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?

With output schema present, description covers prerequisite, usage, and dereferencing behavior; complete for a simple 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 covers the single parameter fully; description adds context about obtaining operationId from list_api_specs and gives an example format.

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?

Description clearly states it 'Retrieves detailed specification of a specific API' with specific verb and resource, and distinguishes from sibling tools like list_api_specs.

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 provides prerequisite (first use list_api_specs) and usage instruction, differentiating when to use 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?

No annotations are provided, so the description carries full burden. It discloses that the tool returns full metadata and HTML template code, allows customization of data values, but warns against modifying iNavi API constructors or adding options. It does not explicitly mention read-only nature but 'retrieve' implies non-destructive. The description adds valuable behavioral context beyond the mere function definition.

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 fairly long but well-structured with clear sections (PREREQUISITE, USAGE, CUSTOMIZATION, IMPORTANT). It front-loads the purpose. While it could be slightly more concise, the structure aids readability for an AI agent.

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 (one parameter, no nested objects, output schema present), the description covers all necessary context: prerequisites, usage, customization rules, and when to use. It is complete for an agent to invoke correctly.

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 'id' parameter. The description adds meaning by providing example ID format ('e.g., marker-basic') and that the ID comes from list_map_examples. This adds value beyond the schema 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 starts with a clear verb and resource: 'Retrieve a specific iNavi Maps HTML example by ID with complete metadata.' It also distinguishes itself from siblings by explaining how it differs from list_map_examples (browsing vs. retrieval) and from get_api_spec (different resource type).

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 states prerequisite: 'Use list_map_examples first to browse available examples and get the ID.' Provides usage instruction and when to use this tool over alternatives: 'Unless the user explicitly requests another map provider... use this tool for visualization requests.'

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 covers behavioral traits: it's a read-only listing tool, notes category may not be as expected, advises retry strategy, and explains that reference document entries behave like regular API entries.

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?

Description is structured with USAGE, FILTERING, IMPORTANT, NOTE sections and is front-loaded. Some redundancy in the IMPORTANT section could be trimmed, but every sentence serves a 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?

With one optional parameter, no required params, high schema coverage, and an output schema present, the description fully covers the tool's role, error handling, and interaction with sibling tools. No gaps remain.

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 rich enum descriptions. The description adds workflow-level guidance (use without category when unsure, retry logic) that goes beyond schema, but the schema already explains categories well.

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 lists available iNavi Maps APIs and can be filtered by category. It uses specific verb 'Lists' and resource, and distinguishes from sibling get_api_spec by indicating a two-step workflow.

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 usage guidance: 'First browse available APIs with this tool, then use get_api_spec to retrieve detailed specifications.' Also includes when to retry without category filter and how to handle reference documents.

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, description fully bears transparency burden. It explains the 'two-tier metadata system', 'lightweight summaries', and mentions returned fields (ID, title, description, tags). However, it does not mention pagination or limits, which could be relevant for a list tool.

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?

Description is well-structured with clear sections (USAGE, FILTERING) and no redundant sentences. Every sentence adds value and is front-loaded with the main 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?

Given the low complexity (1 optional parameter, output schema exists), the description is complete. It covers purpose, usage flow, filtering, and output characteristics. The existence of output schema does not detract from 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 detailed enum descriptions. The description adds minimal extra: emphasizes optionality and a note that 'shapes' are also known as features. Per guidelines, baseline 3 with high coverage; slight extra information does not justify a 4.

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 browses and discovers iNavi Maps HTML examples, with specific verb 'browse/discover' and resource 'examples'. It distinguishes from sibling 'get_map_example' by indicating this is the first step before retrieval.

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 usage guidance: 'Call this tool first to see what examples are available, then use get_map_example with the desired ID.' Also explains filtering by category, providing clear context for when and how to use.

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