无名图书 wuming-books

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

With no annotations, the description carries the behavioral burden itself. The verb '获取' clearly indicates a read-only retrieval, and the field list tells the agent what to expect. It does not mention behavior for invalid or missing ISBNs, but for a simple lookup tool this is a minor gap.

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 efficiently structured sentence: the action and input are front-loaded, followed by a colon and a compact list of returned fields. 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 is simple: one required parameter and no output schema. The description adequately compensates for the missing output schema by listing the returned fields, and the input requirement is clear. It is complete enough for an agent to invoke correctly, though it does not cover error cases.

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 already fully describes the single ISBN parameter at 100% coverage, including the 10-or-13-digit constraint. The description only repeats 'by ISBN' and adds no additional parameter semantics beyond what the schema provides.

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 begins with a specific verb and resource: '按 ISBN 获取图书详情' (get book details by ISBN). It then enumerates the exact returned fields, making the tool's purpose unmistakable and clearly distinguishing it from siblings like search_books or list_book_tags.

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 clearly implies the tool is the right choice when the agent already has an ISBN and needs comprehensive book details. It does not explicitly mention alternatives or exclusions, but the ISBN-based scope is a clear context signal.

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 and does describe the returned content categories, signaling a read-only retrieval. It does not disclose edge-case behavior such as invalid or unknown ISBNs or whether some fields may be empty, which would strengthen transparency.

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 well-structured sentence leads with the lookup key and result type, lists the content components, and ends with the intended user question. Every clause adds information 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 one-parameter read tool with no output schema, the description adequately enumerates the result components and the user need it serves. It is slightly light on failure or format expectations, but nothing critical is missing for tool selection and 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 100% and the single 'isbn' parameter is already documented as 10 or 13 digits. The description only restates that the lookup is by ISBN, adding no meaningful semantic detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states a specific action, '按 ISBN 获取图书的 AI 导读', and enumerates the delivered content: 编辑书评、核心看点、读者共识、章节摘要与热门短评. This makes the tool's function clear, though it does not explicitly contrast with sibling tools such as get_book_detail.

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 a clear use case: answering '这本书讲什么、值不值得读'. It does not name alternative tools or state when not to use this tool, but for a simple single-purpose lookup the context is sufficient.

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 communicates that this is a read-style operation returning recent hot books and that filtering is possible, but it does not clarify how 'hot' is determined, the time window, ordering, or response format. Basic behavior is clear, but meaningful detail is missing.

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 concise sentences: the first states the function and filtering capability, the second states the intended use case. There is no wasted wording, and the key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-style tool with two optional parameters and no output schema, the description covers the purpose, category filtering, and a typical query scenario. It even references list_book_tags for valid tag values. It is arguably complete for invoking the tool, though it could describe the response shape more explicitly.

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 100%, so the schema already documents tag and count well. The description's mention of category filtering adds little beyond the schema, and it does not provide additional meaning about count or tag. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves recently hot updated books and can filter by category, making the core purpose specific and understandable. It does not explicitly differentiate itself from get_toplist or other siblings, so it misses the top score.

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 it fits questions like 'what hot books are there recently,' giving clear usage context. It does not mention when not to use it or compare it with alternatives such as get_toplist, but the stated use case is sufficiently clear for an 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?

With no annotations, the description must carry the behavioral burden. It does convey that the operation is a fetch and explains what kind of lists exist, but it does not describe the return shape, ordering, or any other behavioral details. For a simple read-only list tool this is adequate, though still somewhat thin.

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 dense sentence that front-loads the main purpose and then efficiently lists all supported list types. It is slightly redundant with the schema enum, but the Chinese labels and grouping make the duplication useful rather than wasteful.

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 two optional parameters and all supported list types are covered, which is enough for basic invocation. However, there is no output schema and no statement of what the returned payload looks like, and no guidance is given for distinguishing this tool from get_recent_hot, leaving the agent to make assumptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides full coverage: type has an enum and default, and count has a range and default, so the baseline is 3. The description adds value by mapping the terse enum values to human-readable Chinese labels like 遗珠榜, 新书榜, 法律, and 社科, which clarifies the meaning of 'cold' and the category choices.

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 a specific verb and resource ('获取图书精选榜单') and enumerates nine concrete list types, so the tool's purpose is immediately clear. It does not explicitly name or differentiate sibling tools like get_recent_hot, but the listed categories make the intended scope understandable.

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?

There is no guidance about when to use this tool instead of a sibling such as get_recent_hot, search_books, or list_book_tags. The description only enumerates available list types; it gives no exclusions, prerequisites, or alternative-routing hints.

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 accurately conveys that this is a read-only operation by using '列出' and '返回', and explicitly states the output is links to category pages. It does not mention sorting, limits, or side effects, but for a simple enumeration this is reasonably 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 a single compact sentence that front-loads the main action and includes useful examples of category names. Every word contributes meaningful information, with no filler, repetition, or vague qualifiers.

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 no annotations and no output schema, the description is complete. It states the scope (all categories) and the return value (page links per category), which is everything an agent needs to invoke it correctly. Nothing critical is missing or unexplained.

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 parameters, so schema coverage is effectively not an issue. The baseline for a 0-parameter tool is 4 because there is no parameter semantics for a description to clarify. The description appropriately focuses on the output rather than inputs.

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 function: listing all site categories and returning their page links. It uses a specific verb ('列出') and a distinct resource ('分类'), with examples that leave no ambiguity. This cleanly separates it from sibling tools focused on details, guides, hot lists, toplists, and search.

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 a clear use case: if you need a complete list of book categories and their links, this is the tool to call. No overlap with sibling tools is apparent, and the description gives enough context for an agent to identify when it applies. It stops short of explicitly naming alternatives or exclusions, but none seem necessary here.

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 burden and does disclose the read-only search behavior plus the exact return fields (title, author, publisher, Douban rating, publication date, format, detail link). It does not mention ordering, no-result behavior, or pagination semantics beyond what the schema already provides, which keeps it from a 5.

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 front-load the search criteria, then specify return fields and filtering. Every sentence carries useful information 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 tool with four simple parameters and no output schema, the description covers what to pass, what comes back, and how to obtain valid tag values via list_book_tags. Minor gaps such as result ordering and no-result handling do not block 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 100%, so the baseline is 3. The description restates the query semantics and mentions tag filtering, but it adds little meaning beyond the parameter descriptions already present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete action ('search') applied to a specific resource ('Chinese books') and enumerates the search keys (title, author, ISBN, keyword). It is clearly distinct from siblings such as get_book_detail or list_book_tags.

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 clear context for when to use this tool and points to list_book_tags for valid tag values. However, it does not explicitly state when to prefer search_books over get_book_detail or other alternatives, nor does it give exclusion criteria.

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