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

No annotations are provided, so the description carries full burden. It mentions the tool is for 'browsing document tree structure' which implies read-only behavior, but doesn't explicitly state whether it's read-only, what permissions are required, how results are returned (pagination, format), or any rate limits. For a tool with no annotation coverage, this is insufficient behavioral disclosure.

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 appropriately concise with two sentences in the main description and a clear Args section. The first sentence states the purpose, the second provides usage context. No wasted words, though the structure could be slightly improved by integrating the Args explanation more seamlessly.

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 has an output schema (which handles return values), 1 parameter with basic documentation in the description, and relatively simple functionality (listing child pages), the description is reasonably complete. It covers purpose, basic usage, and parameter meaning. The main gap is lack of behavioral details that would be important for a production 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%, so the schema provides no parameter documentation. The description adds the parameter 'url' with explanation 'Confluence 父页面的完整 URL' (Complete URL of Confluence parent page), which provides basic semantics. However, with only 1 parameter documented out of 1 total, this meets the baseline but doesn't add rich details like URL format requirements or validation rules.

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: '获取 Confluence 页面的子页面列表' (Get a list of child pages for a Confluence page). It specifies the verb ('获取' - get) and resource ('子页面列表' - child page list). However, it doesn't explicitly differentiate from sibling tools like 'get_page_structure' which might provide similar hierarchical information.

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 provides some usage context: '适合浏览文档树结构，找到需要的子页面' (Suitable for browsing document tree structure, finding needed child pages). This implies when to use it (for browsing/finding child pages), but doesn't explicitly state when NOT to use it or mention alternatives like 'get_page_structure' for different structural information.

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 the full burden of behavioral disclosure. It effectively describes key behaviors: the tool fetches and converts content to Markdown, preserves document structure (headings, tables, code blocks, lists), and supports specific URL formats. However, it doesn't mention potential limitations like authentication requirements, rate limits, or error conditions, which would be helpful for a tool interacting with an external service.

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 and appropriately sized. It starts with the core purpose, then provides URL format details, output characteristics, and usage guidance. Each sentence adds value, though the final usage guidance sentence could be slightly more concise. Overall, it's efficient and front-loaded with 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?

Given the tool's moderate complexity (fetching and converting external content), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose, parameter details, output format, and usage context. The main gap is lack of behavioral constraints like authentication or error handling, but the output schema reduces the need to describe return values.

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 significant value beyond the input schema, which has 0% description coverage. It explains the 'url' parameter in detail: listing three supported URL formats with examples, clarifying what constitutes a valid input. This compensates fully for the schema's lack of documentation, providing essential context the schema alone doesn't offer.

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: '获取 Confluence 页面的完整内容，转换为 Markdown 格式' (get Confluence page's complete content, convert to Markdown format). It specifies both the verb ('获取' - get) and resource ('Confluence 页面' - Confluence page), and distinguishes from siblings like get_child_pages or get_page_attachments by focusing on full content extraction with format conversion.

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 provides explicit usage guidance: '拿到内容后，你可以根据内容回答用户的问题，如果内容中找不到答案就回复不知道' (After getting the content, you can answer user questions based on the content; if the answer isn't found in the content, reply 'don't know'). This tells the agent when to use this tool (to extract content for answering questions) and what to do with the output. It also implicitly distinguishes from siblings by focusing on content extraction rather than structure or attachments.

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 mentions the tool retrieves attachment lists but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, error conditions, or what happens with invalid URLs. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond the basic operation.

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 appropriately concise with two sentences: one stating the purpose and another defining the parameter. It's front-loaded with the core functionality. However, the second sentence is somewhat redundant as it repeats 'url' without adding substantial value beyond what's implied by the 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 tool has an output schema (which handles return values), 1 parameter with 0% schema coverage, and no annotations, the description is minimally adequate. It covers the basic operation but lacks context on usage guidelines, behavioral details, and differentiation from siblings. For a simple read operation, it meets the minimum but doesn't provide a complete picture for optimal agent use.

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 minimal parameter semantics: it states 'url: Confluence 页面的完整 URL' (url: complete URL of Confluence page). With 0% schema description coverage and only 1 parameter, this provides basic context. However, it doesn't elaborate on URL format requirements, validation, or examples. The baseline is appropriate given the single parameter and lack of schema descriptions.

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: '获取 Confluence 页面的附件列表（图片、文档等）' (Get attachment list for Confluence pages). It specifies the verb ('获取' - get) and resource ('附件列表' - attachment list) with examples. However, it doesn't explicitly differentiate from sibling tools like 'get_page_images' which might overlap in 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 provides no guidance on when to use this tool versus alternatives. With siblings like 'get_page_images' (which might return only images) and 'get_confluence_page' (which might return page content including attachments), there's no indication of when this specific attachment-list tool is preferred. The description only states what it does, not when to choose it.

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 does well by disclosing key behaviors: it downloads images (implies network/IO operation), returns them for analysis, and provides metadata (filename, alt text, heading). It doesn't mention rate limits, permissions, or error handling, but covers core functionality adequately.

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 and front-loaded with the core purpose. Each sentence adds value: first states action, second explains LLM capability, third provides usage guidelines, fourth details return format, and fifth documents parameters. 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?

For a 2-parameter tool with no annotations or output schema, the description is quite complete: it covers purpose, usage, behavior, and parameters. It could mention output structure more explicitly (e.g., list of objects) or error cases, but given the context, it's largely 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?

Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'url' as 'Full Confluence page URL' and 'max_images' with its default and purpose. This adds clear meaning beyond the bare schema, though it could specify URL format or 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 specific action ('Download images from a Confluence page') and resource ('images'), distinguishing it from siblings like get_confluence_page (text content) or get_page_attachments (files). It explicitly mentions the purpose is for 'visual analysis' of diagrams, screenshots, etc., making the scope distinct.

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 provides explicit 'Use this when' guidelines with three concrete scenarios (user asks about diagrams, need to understand visual content, text insufficient). It implicitly distinguishes from siblings by focusing on visual analysis versus text-based tools, though it doesn't name specific 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?

No annotations are provided, so the description carries the full burden. It describes what the tool returns (structure overview with specific elements like tables/code/images), which is helpful behavioral context. However, it doesn't mention potential limitations (e.g., authentication needs, rate limits, error conditions, or what '结构概览' precisely entails beyond listed elements). The description doesn't contradict any annotations since none exist.

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 highly concise and well-structured. It uses two sentences: the first states the purpose and key return elements, the second provides usage guidance. The 'Args:' section cleanly documents the parameter. Every sentence earns its place with no wasted words, and information is front-loaded (purpose first, then usage).

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 moderate complexity (single parameter, no annotations, but with an output schema), the description is reasonably complete. It explains the tool's purpose, usage context, and parameter semantics. Since an output schema exists, the description doesn't need to detail return values. However, it could better address behavioral aspects like error handling or permissions, and more explicitly differentiate from sibling tools.

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 description coverage is 0% (no descriptions in schema), but the description compensates well. It explicitly documents the single parameter 'url' with 'Confluence 页面的完整 URL' (complete URL of Confluence page), adding crucial semantic meaning beyond the schema's bare 'string' type. This fully addresses the parameter's purpose, though it doesn't specify format constraints (e.g., URL validation).

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: '获取 Confluence 页面的结构概览，包括目录大纲、是否包含表格/代码/图片等信息' (Get an overview of Confluence page structure, including table of contents outline, and whether it contains tables/code/images). It specifies the verb ('获取' - get) and resource ('Confluence 页面结构' - Confluence page structure), but doesn't explicitly differentiate from sibling tools like get_confluence_page or get_child_pages beyond mentioning it's for '结构概览' (structure overview) rather than full content.

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 provides clear context on when to use this tool: '适合在获取完整内容前，先了解页面结构' (Suitable for understanding page structure before obtaining full content). This gives a specific use case (preview before full retrieval) but doesn't explicitly mention when NOT to use it or name alternatives among the sibling tools (e.g., use get_confluence_page for full content instead).

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 the full burden. It explains the retrieval method (BM25 keyword retrieval), document segmentation (paragraphs/tables/code blocks), and that it returns the most relevant snippets. However, it doesn't mention important behavioral aspects like whether this is a read-only operation, what permissions might be needed, rate limits, or error conditions. The description adds some context but leaves significant gaps.

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 and efficiently written. It starts with the core purpose, explains the method and segmentation, provides usage guidelines, and then clearly documents parameters. Every sentence adds value, and the information is front-loaded with the most important details first.

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 that there's an output schema (which handles return values), no annotations, and 3 parameters with 0% schema coverage, the description does a good job explaining the tool's purpose, usage guidelines, and parameter meanings. However, for a search tool with no annotations, it could provide more behavioral context about what constitutes a 'snippet' and how relevance is determined.

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?

With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. The description provides clear explanations for all three parameters: 'url: Confluence 页面的完整URL' (complete URL of Confluence page), 'question: 用户的问题或搜索关键词' (user's question or search keywords), and 'top_k: 返回最相关的片段数量，默认5个' (number of most relevant snippets to return, default 5). This adds substantial value beyond the bare 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's purpose: '在 Confluence 页面中搜索与问题相关的内容片段' (search for content snippets related to a question in a Confluence page). It specifies the method (BM25 keyword retrieval), document segmentation approach (paragraphs/tables/code blocks), and distinguishes it from sibling tools by mentioning when to use get_confluence_page instead.

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 provides explicit guidance on when to use this tool vs. alternatives: '对于较短的文档（<5000字），建议直接使用 get_confluence_page 获取全文。对于较长的文档，使用此工具可以更精准地找到相关内容。' It clearly states this tool is for longer documents where precise information location is needed, while get_confluence_page is better for shorter documents.

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