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

With no annotations provided, the description carries the full behavioral burden. It discloses automatic range calculation, rejection on match failure, invalid style value '3', default values, and return value semantics. This is solid transparency for a creation tool, though it does not mention duplicate-bookmark behavior or idempotency.

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 compact: critical constraint first, then enum mappings/defaults, then return-value usage. Every sentence earns its place with no filler or 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?

For a 5-parameter tool with no annotations and no schema descriptions, the description covers the essential custom logic, valid values, defaults, and post-return usage. The main gaps are explicit semantics for book_id/chapter_uid and behavior when a duplicate bookmark already exists, but the output schema presumably covers return shape.

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 does well by explaining abstract's verbatim constraint and enumerating color_style/style numeric meanings and defaults. However, book_id and chapter_uid are left to their self-explanatory names, with no additional context provided.

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 identifies the action as creating a highlight/bookmark tied to a chapter, and specifies the key requirement that abstract must be verbatim. It also distinguishes itself from siblings like update_bookmark_style and remove_bookmark by noting the returned bookmarkId is used for those operations.

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?

It explains when the tool will reject a request (verbatim match failure) and gives the default style/color behavior. It does not explicitly enumerate when to prefer this over alternatives, but the reference to using the returned bookmarkId for style changes/deletion gives practical routing 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?

With no annotations, the description carries the full behavioral burden. It does disclose one genuinely useful behavioral trait: 'content 前自动加 🌕 署名' (🌕 attribution is automatically prepended to content), which prevents the agent from duplicating the prefix. However, for a mutation tool it says nothing about auth requirements, idempotency, duplicate handling, or side effects beyond the prefix behavior.

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?

A single compact sentence with zero filler. The most decision-relevant information (chapter-level scope, no citation, auto-attribution) is front-loaded, and every clause earns its place.

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?

Has an output schema, so return-value documentation is covered. For a simple three-string-parameter create tool, the description is mostly adequate: scope and auto-prefix behavior are disclosed. However, it omits operational details an agent might need, such as whether the chapter must belong to the given book_id or any content constraints, leaving minor gaps for a simple mutation 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 description must compensate, but it only indirectly illuminates the content parameter via the auto-prefix note and the chapter-scope context. It adds no meaning for book_id, chapter_uid, or their relationship (e.g., that the chapter must belong to the book). The parameter names are self-evident, but the description fails to bridge the 0% schema coverage gap.

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 identifies a specific action: adding a chapter-level thought/review attached to the whole chapter with no original-text citation. This distinguishes it from sibling review tools like add_review and add_comment. It stops short of 5 because it never states the verb+resource directly (e.g., 'adds a review to a chapter') and relies on characteristic descriptions rather than an explicit statement of what the tool does.

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?

Usage context is implied through the parenthetical '挂在整章上，无原文引用' (attached to the whole chapter, no original text citation), which signals when this tool is appropriate versus a citation-based or book-level review. However, no alternatives are named and there is no explicit when-to-use/when-not-to-use guidance, leaving routing decisions to inference.

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 the full behavioral burden and it clearly discloses two non-obvious behaviors: content is automatically prefixed with a 🌕 signature, and reply_comment_id triggers quote-mode reply without nested threading. It does not mention side effects or permissions, but these are not likely blockers for a simple comment 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 two short sentences, front-loaded with the core action, and every clause adds information. The reply_comment_id semantics are compactly placed without excess.

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 low-complexity tool with an output schema, it covers the main action, auto-behavior, and reply mode. The primary missing piece is the meaning/format of review_id and explicit tool-selection guidance, but the description is otherwise 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 content (auto-prefix) and reply_comment_id (reply/quote mode), but does not explain review_id, which is required. The title 'Review Id' gives only weak signal, leaving a notable gap.

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 action and resource: '在想法下发评论' (post a comment under an idea). It distinguishes from sibling tools by targeting comments rather than reviews/chapters, though it does not explicitly name the alternatives.

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?

It provides a concrete condition for the optional parameter: 'reply_comment_id 非空即回复某条评论' (non-empty means reply to a comment), which is useful. However, it gives no explicit guidance on when to choose add_comment over sibling tools such as add_review or list_comments.

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 behavioral disclosure burden. It discloses two important behaviors beyond the schema: abstract must be an exact quote and the tool rejects writes on match failure, and content is automatically prefixed with a 🌕 signature. This gives the agent useful expectations for side effects and validation.

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 short sentences contain purpose, constraints, side effects, and alternate-tool routing with no filler. The key behavioral constraints are front-loaded, and the sibling reference is a separate efficient sentence.

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 tool with four straightforward parameters and an output schema, the description covers the critical behavioral constraints and alternative routing. It does not spell out book_id and chapter_uid semantics, but their meaning is reasonably inferable from names and the chapter-focused context.

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 for parameter meaning. It meaningfully clarifies abstract and content, but book_id and chapter_uid are left entirely implicit. The context makes them inferable, but they are not explicitly described.

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 opens with the specific action '写想法' (write a thought) and clearly names the resource being acted on. It also distinguishes itself from the sibling tool by explicitly directing chapter-level thoughts to add_chapter_review, so an agent can tell them apart immediately.

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 gives explicit routing guidance: chapter-level thoughts should use add_chapter_review instead. It also communicates the key condition for use—abstract must be a verbatim quote from the chapter—which tells the agent when this tool is appropriate.

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 the full burden of explaining behavior. It discloses one useful behavior (chapter_uid=0 searches the entire book), but it does not explicitly state that this is a read-only listing, how highlights are ordered/scored, or what '选句素材' implies about the returned content.

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 one compact sentence with no filler; the key parameter behavior is placed in a parenthetical. It is economically written, though the parenthetical style makes it feel more like a note than a structured definition.

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 two-parameter tool with an output schema, the core invocation is roughly covered: book_id is required and chapter_uid=0 fetches the whole book. However, the description still omits when the tool should be chosen over sibling tools and leaves the purpose slightly implicit, so it is only minimally complete.

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 partially explains chapter_uid via the 0=whole-book behavior, but book_id is left to the reader and no format or value semantics are given.

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 identifies the tool as returning popular highlights (热门划线) intended as sentence-selection material, which is a specific resource and purpose. It does not use a verb like 'list' or 'fetch', but the resource is clear enough and the 'best'/'热门' framing separates it from review and bookmark tools.

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 given on when to use this tool instead of sibling bookmark/reader tools such as get_reader_bookmark, add_bookmark, or list_comments. The only usage hint is the parenthetical that chapter_uid=0 queries the whole book, which is a parameter behavior, not a decision rule.

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 the behavioral burden. It discloses cache-first behavior and that refresh=True forces a re-fetch, which is concrete operational guidance. It omits auth/error details, but those are less critical for a read 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?

Extremely compact; every clause adds value: output content, caching behavior, and usage timing. Front-loaded with the primary purpose before operational 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 an output schema exists, not detailing return values is acceptable. The description provides enough context for an agent to select and invoke the tool, though 'co index' is left somewhat undefined and the relationship to sibling tools is only implicit.

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 the description must compensate. It explains the refresh parameter's semantics (cache-first by default, refresh=True forces a new fetch), but book_id and chapter_uid are left to their self-explanatory names without additional detail.

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?

States a specific action and resource: retrieving chapter plaintext plus a 'co index'. This clearly distinguishes it from TOC, shelf, and progress siblings, though it does not explicitly name an alternative tool.

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 an explicit when-to-use instruction: '共读前先读这个' (read this first before co-reading). It gives clear context but does not describe exclusions or alternative tool choices.

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 burden of behavioral disclosure. It explicitly declares the operation as read-only and clarifies that it returns real user progress, not AI co-reading progress. It does not discuss auth, rate limits, or data freshness, but for a simple read tool with an output schema this is fairly strong 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 a single compact sentence that front-loads the core purpose, adds the read-only qualifier, and names the alternative tool. Every part earns its place 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?

The tool has only one required parameter, an output schema, and a clear sibling distinction. The description covers purpose, read-only behavior, and alternative routing, which is complete for a tool of this simplicity.

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%, and the description does not explain book_id or how it relates to the progress being fetched. The parameter name is somewhat self-explanatory, but the description adds no meaning beyond the schema's title.

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 identifies the resource as the user's real reading progress, states the operation is read-only, and explicitly distinguishes it from get_reader_bookmark, which covers AI co-reading progress. This fully disambiguates the tool from its closest sibling.

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 states that AI co-reading progress should use get_reader_bookmark instead and stresses that the two must be kept strictly separate. This provides clear when-to-use and when-not-to-use guidance with the alternative named directly.

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 must carry the behavioral load. It discloses that the data is local and independent from WeChat Reading progress, and that the no-parameter call returns all titles. It does not explicitly state read-only/no side effects, permissions, or error behavior, but the 'get/return' language strongly implies a query operation. This adds meaningful context but leaves the safety profile implicit.

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?

One compact sentence, front-loaded with purpose and scope, then the invocation note. Every clause earns its place; no filler or repetition.

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 output schema exists, so return-value documentation is already available. The description covers the primary no-parameter call path and the local nature of the data. The main gap is the effect of book_id and the relationship to sibling tools, which an agent would need to infer. For a low-complexity tool with one optional param, this is adequate but not comprehensive.

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 the description must compensate. It clarifies that omitting book_id returns all books, which is the key semantic for the only parameter. However, it does not explain what happens when book_id is supplied (e.g., filtering to one book), so compensation is partial.

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 identifies the resource as the AI reading companion's local progress and explicitly distinguishes it from WeChat Reading's real progress. It also states that calling without parameters returns the full book list. However, it does not directly name sibling tools like get_progress or set_reader_bookmark to differentiate from them, so it stops short of full sibling-level 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?

It provides an explicit invocation hint ('不带参返回全部书目' – return the full list without parameters) and contextualizes the tool as local-only, which helps an agent decide when this tool fits. But it offers no explicit when-to-use vs alternatives or any exclusion criteria, leaving comparison with get_progress/get_shelf to inference.

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 the behavioral burden. '书架列表' strongly suggests a read-only list operation and '官方通道' hints at the data source, but the description does not disclose authentication requirements, scoping to the current user, or error/pagination behavior. This is acceptable for a simple getter but not fully 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 very short and front-loads the core term, which is concise. However, '官方通道' is an unexplained parenthetical that may add confusion rather than clarity, and the description is a fragment rather than a well-structured sentence.

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 zero-parameter tool with an output schema, the core purpose is mostly covered. Still, the description omits context about whose bookshelf is returned, whether authentication is needed, and what 'official channel' means relative to the sibling tools, leaving the agent to infer these details.

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 has zero properties, so there are no parameter semantics to document. The description reinforces that the tool simply returns a bookshelf list without arguments, satisfying the baseline for a no-parameter tool.

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 the resource ('书架列表' = bookshelf list) and clearly implies the operation of listing it, matching the tool name get_shelf. It is distinguishable from siblings like get_toc and get_progress because it uniquely targets the bookshelf. The '官方通道' qualifier adds a channel context but is not needed to understand the core 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 the tool should be used when an agent needs a bookshelf list, and no sibling tool appears to provide the same function. However, it gives no explicit when-to-use guidance, exclusions, or alternatives, and the meaning of 'official channel' is not explained.

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 burden. It discloses the return shape and emphasizes that chapterUid from here must be used for other operations. It does not reveal side effects, ordering, pagination, or failure behavior, but for a simple read-only TOC call this is acceptable.

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 one compact sentence with the result shape front-loaded and the important usage note immediately after. No filler or redundant wording.

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?

An output schema exists, so return values are covered. The description adds the key contextual fact that chapterUid is the required linkage for writing thoughts and reading. It could mention the relationship to get_shelf or get_chapter_text more explicitly, but for a simple TOC tool this is 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%, and the description does not explain book_id, where it comes from, or how to validate it. The parameter is self-evident from its name and schema, but the description adds no meaningful semantic detail beyond that.

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 this tool returns the book's table of contents with chapterIdx, chapterUid, and title fields. It also notes chapterUid is the canonical identifier for writing thoughts and reading, which helps distinguish its role from sibling tools like get_chapter_text.

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 when to use this tool: before writing thoughts or reading, you need the chapterUid from this table of contents. However, it does not explicitly name alternatives or state when not to use it, leaving some inference to the agent.

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 more weight. It discloses a useful behavioral detail: comment IDs follow the pattern {reviewId}_c{...}, which is critical for replying to comments. It does not mention pagination or ordering, but for a simple list operation this is acceptable.

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 efficient sentence that front-loads the core purpose and then adds the useful ID-format context. 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 low-complexity list tool with an output schema present, the description covers the essential purpose, target resource, and a key usage note. It omits things like pagination, but the output schema likely carries return details, and the description is adequate for correct invocation.

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 for the lone review_id parameter. It implies review_id identifies the thought/review by saying '某条想法下', but it does not explicitly define the parameter or its format. Some meaning is added, but not 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?

The description clearly states the tool lists comments under a specific thought/review, with a specific resource ('某条想法下的评论列表'). It also distinguishes itself from siblings like add_comment by focusing on retrieval rather than creation.

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 says '回复评论时用它' (use it when replying to comments), giving a clear usage context. It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to know when this tool is relevant.

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 behavioral transparency burden. It discloses user scope ('自己') and book scope ('此书'), which are useful traits, and implies a read-only retrieval. However, it does not explicitly state what items are returned or any limitations, leaving some ambiguity.

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 compact sentence that conveys scope and purpose with no filler. The parenthetical adds high-value usage guidance without unnecessary length.

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 one-parameter getter with an output schema, this is mostly complete: it identifies the entity (own thoughts for a book) and the intended workflow. The main gap is a more formal statement of what '想法' includes, such as reviews versus comments or annotations, which matters given the many related 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 has one required parameter, book_id, with 0% schema description coverage. The description's '此书' loosely maps to the book identifier, but it does not explain the parameter's format, meaning, or usage. With such low schema coverage, the description provides insufficient compensation.

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 phrase '自己在此书的全部想法' indicates the tool returns the user's own thoughts/reviews for a specific book, and '写前防重复' clarifies the retrieval purpose. It distinguishes itself from add_review and list_comments by emphasizing own content, though it lacks an explicit verb like 'get/list'.

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 parenthetical '写前防重复、延续语气' explicitly states the intended use case: before writing a review, to avoid duplication and maintain consistent tone. It does not name alternatives or exclusion cases, but for a simple read-style retrieval tool the context is reasonably clear.

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 transparency burden. It discloses that the tool packages several read-oriented data sources and positions it as a non-authoritative convenience utility. It does not explicitly state that it is read-only or mention any side effects, auth needs, or performance implications.

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 two short sentences with no filler. The component list is front-loaded, and the usage caveat is stated in the second sentence. Every part earns its place.

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?

An output schema exists, so return-value details are not required in the description. The description states the tool's purpose and a key usage constraint, but it omits guidance on when to choose this aggregate over the individual sibling calls and leaves parameter semantics entirely to the 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 description coverage is 0%, and the description does not explain book_id or chapter_uid at all. The parameter names are self-explanatory, but the description adds no meaning beyond the input schema, so it fails to compensate for the low schema coverage.

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 presents the tool as a convenient bundle ('便捷打包') of specific components: real progress, shared bookmarks, chapter plain text, existing ideas, and popular highlights. This conveys the resource and scope, and distinguishes it from the individual sibling tools by being a composite read package, though it does not name any sibling explicitly.

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 second sentence gives an explicit usage boundary: this is only a convenience tool and must not be treated as the default reading context; context organization belongs to the caller/frontend. However, it does not explicitly state when to prefer this tool over the individual sibling getters or name 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 bears the full burden of behavioral disclosure. It only says 'delete the underline' and does not disclose whether deletion is permanent, whether it removes associated data, how errors are handled, or whether ownership or special permissions are required.

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 extremely compact and front-loaded, with no filler or redundancy. It is arguably too terse given the missing behavioral and parameter context, but as pure conciseness and structure it is 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?

This is a simple one-parameter delete operation and an output schema exists, so the return value need not be explained. However, with no annotations, no usage guidance, and zero parameter documentation, the description is only minimally viable rather than fully contextual.

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%, and the description does not enrich bookmark_id beyond its schema title. It does not explain the expected format, how to obtain a valid ID, or whether it refers to a highlight line, a reader bookmark, or some other entity.

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 Chinese description '删除划线' (delete the highlight/underline) names a concrete verb and resource, making the core action unambiguous. It clearly contrasts with sibling tools like add_bookmark and update_bookmark_style, though it does not explicitly discuss its relationship to related retrieval tools.

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 gives no guidance on when to use this tool versus alternatives such as add_bookmark, update_bookmark_style, or get_reader_bookmark. It does not state any prerequisites, such as the bookmark needing to already exist or how the caller should obtain the bookmark_id.

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 of behavioral disclosure. It adds one useful trait: the operation does not affect the user's real progress. However, it does not mention whether repeated calls overwrite existing co-reading progress, permissions, or other 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 a single efficient sentence that fronts the core action and then adds a critical scoping clarification in parentheses. Every word earns its place, and it is immediately clear what the tool does.

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?

Despite having an output schema, the description is incomplete as an invocation guide. The parameter semantics are unclear, especially the presence of both chapter_uid and chapter_idx with a default empty value. An agent would need to infer the identifier roles from parameter names alone, which is risky.

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 but barely does. It implies a chapter is specified via '读到哪一章', but it does not explain book_id, chapter_uid, or the optional chapter_idx or how they relate. This is inadequate for correctly populating all 3 parameters.

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 uses a specific verb and resource: '记录 AI 共读伙伴读到哪一章' states that it records the co-reading partner's chapter progress. It also explicitly distinguishes itself from user progress tools with '不影响用户真实进度', which separates it from siblings like add_bookmark and get_progress.

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 when to use the tool: whenever the AI co-reading partner's progress needs to be saved. It does not name alternative tools or provide any explicit when-not-to-use guidance, aside from hinting that this is separate from the user's real progress.

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?

在没有任何注解的情况下，描述较好地承担了行为披露责任：明确这是修改操作、说明部分更新语义，并警告 style 值为 3 时无效。虽然没有提及权限或可逆性，但对这种小型样式更新工具来说已经足够。

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?

两句话没有冗余，第一句说明目的和数据来源，第二句给出参数映射和无效值警告。每个信息点都对调用有直接帮助。

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?

对于只有 3 个参数、无注解且有输出 schema 的简单更新工具，描述已覆盖用途、ID 来源、部分更新行为和全部取值语义。缺少明确“不要在未创建 bookmark 时调用”之类的排斥条件，以及更精确的值类型说明，因此不是满分。

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?

输入 schema 的 description 覆盖率为 0%，描述对此做了有效补偿：列出了 colorStyle 的 1-5 颜色映射、style 的 0/1/2 映射，并解释 bookmark_id 的来源。缺点是用 colorStyle 而非 schema 中的 color_style，且未说明数字应以字符串还是整数传输。

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?

描述以明确动宾结构开头：“改已有划线的样式”，即更新已存在的 bookmarks 样式，并指出 bookmarkId 来自 add_bookmark 的返回。这使它和 add_bookmark、remove_bookmark 等兄弟工具明显区分开来。

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?

描述说明了使用场景是对已存在的划线做部分更新，以及“只传想改的字段”这一关键约定。虽然没有显式列举何时不该用或列举替代工具，但“已有”和“来自 add_bookmark”已经提供了足够的上下文。

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