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

No annotations provided, so description carries full burden. It mentions fetching from data source for note_id and lists return fields (sentiment, hooks, etc.), but lacks details on error handling, behavior when both parameters provided, or auth requirements.

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 and front-loaded with purpose, then methods. The Args block adds structure, but some redundancy could be removed.

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 all optional parameters, the description covers what the tool does, its inputs, and outputs. Lacks edge-case behavior but sufficient for an analytical 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 0%, but the description adds meaning: explains note_id fetches from source, content is for direct analysis, and title is used with content. This compensates for missing 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 analyzes a note's structure, sentiment, and engagement patterns. It distinguishes from siblings like rednote_get_note_detail (raw content) and rednote_extract_patterns (pattern extraction) by focusing on deeper analysis.

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 explains two usage modes (by note_id or direct content), which guides when to use each. However, it does not explicitly state when to avoid this tool in favor of siblings like rednote_get_note_detail.

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, so description bears full burden. Discloses that it searches and analyzes notes collectively, and lists specific extracted outputs. Does not mention destructive actions or rate limits, but the scope is clear and safe.

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 paragraphs plus an 'Args' section. Front-loaded with main purpose. Concise, but the structure could be more streamlined. No wasted sentences.

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 2 parameters, no output schema, and no annotations, the description provides a reasonable understanding of tool behavior and inputs. Could mention return format, but not required.

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 0%, but description adds examples for query (e.g., '美股投资') and explanation for limit (default 20). Compensates well for missing 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?

Clearly states verb 'extract', resource 'common patterns from multiple RedNote notes', and topic analysis. Differentiates from siblings like rednote_analyze_note (single note) and rednote_search_notes (search only).

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?

Describes when to use: to identify title patterns, content structures, common tags, etc. from multiple notes. Does not explicitly state when not to use or mention alternatives, but siblings list provides 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, so description carries the burden. It explains the output and style options but does not disclose behavioral traits like AI usage, creative limits, or error handling.

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, front-loaded with the purpose, and uses clear structure with line breaks and an 'Args' section, making it easy to scan.

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 4 parameters, no output schema, and no annotations, the description covers the essentials: output components, style examples, and parameter explanations. However, it could be more explicit about the output format (e.g., JSON structure).

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 0%, but the description compensates by listing arguments with examples (e.g., '美股入门') and explaining style enums ('干货', '情绪', etc.), adding value beyond the schema's titles and defaults.

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 generates a RedNote post outline with specific elements (title, content outline, hashtags, posting tips) and distinguishes from sibling tools like rednote_analyze_note and rednote_extract_patterns.

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 the tool is for generating post outlines but does not explicitly state when to use it versus alternatives, nor does it mention exclusions or prerequisites.

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?

Describes retrieval operation with no side effects, but lacks details on authentication, rate limits, or potential errors. With no annotations, the description is minimally 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?

Concise, front-loaded purpose, and structured Args section. Every sentence adds value with no redundancy.

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 simple parameters and no output schema, the description sufficiently covers return data (content, metrics, author, comments) and parameter behavior.

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 0%, so description compensates by explaining note_id as unique ID and include_comments as optional flag for comments. Adds meaning beyond schema types.

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 'Get full details of a specific RedNote note.' and lists the data retrieved (content, engagement, author, comments), distinguishing it from sibling tools like rednote_search_notes or rednote_analyze_note.

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?

Implicitly indicates use for retrieving details, but no explicit guidance on when not to use or comparison to alternatives like rednote_search_notes for listing or rednote_analyze_note for analysis.

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 says 'rewrite content' and 'provides guidelines', creating ambiguity about whether the tool returns rewritten content or just guidelines. It does not disclose whether content is modified, authentication needs, rate limits, or error handling. This is insufficient for a rewriting 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?

The description is concise and front-loaded with the key action. The summary line is followed by a clear parameter list. Every sentence adds value; no fluff. It achieves efficiency without sacrificing clarity.

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 should explain the return format. It ambiguously says 'provides guidelines' but doesn't specify if the output is rewritten text or step-by-step instructions. It also doesn't mention error conditions, prerequisites, or limitations. It covers parameters and style options, but lacks output specification.

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 provides docstring-style explanations for each parameter: 'content: The original content to rewrite', 'style: Target style - ...', 'reference_note_id: Optional note ID to use as style reference'. This adds meaning beyond the schema, which has no descriptions and only names/types. It covers all three parameters 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 'Rewrite content in RedNote style' with a specific verb and resource. It distinguishes from siblings like generate_post (which creates new posts) and analyze_note (which analyzes). The mention of 'proper formatting and hooks' gives a precise purpose.

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 when you have existing content and want a RedNote-style rewrite. It lists style options ('干货', '情绪', etc.) that suggest scenarios, but it does not explicitly state when to use this tool versus alternatives or when not to use it. No 'if you need X, use Y' 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?

No annotations are provided, so the description must carry the full burden. It discloses sorting options, language support, and the ability to limit results. However, it lacks details on pagination, authentication needs, or whether the tool is read-only.

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: a brief introductory paragraph followed by clean parameter documentation. Every sentence adds value, with no wasted words. The parameter section is structured and easy to scan.

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 tool has no output schema, and the description does not explain the return format (e.g., list of note IDs or summaries). For a search tool, this is a notable gap. However, the parameter documentation is complete, and the purpose is clear.

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 0% coverage (no descriptions in the schema), but the description compensates fully with detailed explanations for each parameter: query with examples, sort with enumerated values, and limit with range and default. This adds significant 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 searches RedNote notes by keyword or topic, using a specific verb ('Search') and resource ('RedNote notes'). It distinguishes from sibling tools like rednote_get_note_detail (which retrieves a single note) and rednote_generate_post (which creates 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 a clear purpose but does not explicitly guide when to use this tool versus alternatives. No exclusions or comparative guidance is given, though it is implied that this is the go-to for searching notes.

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