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

Annotations already declare the safe read-only, idempotent, open-world profile, so the bar is lower. The description adds genuine context beyond that: timeout behavior, network-failure messaging, and the empty-result case with advice to change keywords, which is useful operational detail.

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 purpose is front-loaded, and the Args/Returns/Examples/Error Handling structure is easy to scan. The three usage examples largely repeat the schema defaults and could be trimmed, but nothing is bloated.

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 no output schema, the description does list the returned fields (标题、公司、作者、摘要、时间) and covers failure modes, both required for an agent to interpret results. Missing only pagination/end-of-list behavior for the page parameter.

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 all three parameters are already documented in the schema, including the enum for response_format. The description restates them with examples but adds no syntax or constraint details beyond the schema, so the baseline applies.

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 verb+resource (浏览牛客网面试经验) with the key filter (按公司名筛选), so an agent knows exactly what it retrieves. It does not explicitly differentiate itself from siblings like nowcoder_search or nowcoder_get_discussion, which is the only gap.

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 examples show how to call it, but nothing states when to prefer this over nowcoder_search or nowcoder_get_discussion, and there are no exclusions or prerequisites. Usage context is only implied by the tool name.

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?

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: it enumerates what the result contains (title, author, time, body, tags, link) and documents failure modes (page-load timeout, network failure). No rate limits or auth requirements are mentioned, keeping 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?

Front-loaded one-line purpose followed by clearly labeled Args, Returns, Examples, and Error Handling sections; no sentence is wasted. It is slightly longer than strictly necessary because the examples repeat the same call twice with only the format changed.

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 read-only two-parameter tool with no output schema, the description covers return contents and error behavior, which is what an agent needs. It omits any mention of very long posts or truncation, so it is strong but not exhaustive.

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 schema already documents accepted URL/ID formats and the response_format enum with default. The description's concrete example strings are helpful but largely restate the schema. Baseline 3 is appropriate when the schema carries the parameter burden.

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 verb+resource: retrieve the full content of a Nowcoder discussion post or feed item. The scope ('完整内容') and the object ('讨论帖或动态') are clear, and it is naturally distinct from siblings like nowcoder_search or nowcoder_get_problem. It does not, however, explicitly contrast itself with those siblings, so it stops short of a 5.

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 is implied by the name and by the examples, which show when to call it (fetch one post's detail). There is no explicit statement of when to prefer this over nowcoder_search or nowcoder_get_hot_topics, nor any exclusion or prerequisite guidance. Adequate but leaves the routing decision 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?

Annotations already declare readOnlyHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description earns credit by adding behavior beyond the annotations: the return shape (max 20 items, title + link) and explicit error paths (timeout, network failure, empty results). It does not explain caching or rate limits, so it stops short of 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?

Front-loaded one-line purpose, then clearly labeled Returns/Examples/Error Handling sections — easy to scan. Slightly padded (the Examples line mostly repeats the no-parameter fact already stated), but no meaningful waste.

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?

There is no output schema and no parameters, so the description must carry the return contract — and it does, specifying item count, fields, and failure modes. An agent has enough to call it and interpret results; only pagination/staleness of 'hot' data is unaddressed.

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 tool takes zero parameters and the description confirms no input is required ("无需参数，直接调用即可"). With no parameters to document, the baseline 4 applies.

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+resource: fetching Nowcoder's current hot discussions and topics. An agent can tell this apart conceptually from list_problems or search, but the description never actually names or differentiates any sibling tool. Clear purpose, no explicit sibling differentiation.

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?

"无需参数，直接调用即可" addresses invocation, not selection — it never says when to prefer this over nowcoder_get_discussion, nowcoder_search, or nowcoder_browse_interview. No alternatives, no when-not-to-use 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description goes beyond them by disclosing failure behavior: an error message when the problem does not exist and a timeout message when the page fails to load, which is genuinely useful operational context.

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?

Purpose is front-loaded in the first sentence, then structured into Args/Returns/Examples/Error Handling sections that are easy to scan. The Examples block is somewhat redundant with the schema, costing a little density, but nothing is padded or vague.

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 no output schema, the description must describe the return payload, and it does (标题、时间/内存限制、题目描述), which matches the stated purpose. Failure modes are also covered. It stops short of describing pagination or content-length limits, which is a minor gap for a single-item fetch.

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 schema already documents problemId's format and the markdown/json enum with defaults. The Args section mostly restates this, adding only the 'markdown is default' note that the schema default already encodes. Baseline 3 is correct since the schema does the heavy lifting.

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 (获取牛客网特定编程题目的完整描述) and enumerates what the payload contains (题面、输入输出格式、示例和限制). It implicitly distinguishes itself from list/search siblings by being a single-problem fetch keyed on problemId, but it never names those siblings 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?

There is no when-to-use guidance relative to alternatives such as nowcoder_search or nowcoder_list_problems, and no stated prerequisite for how a problemId is obtained. The Examples block shows invocation syntax rather than selection guidance, so an agent must infer when this tool is the right choice.

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?

Annotations already declare readOnly/idempotent/openWorld/non-destructive, so the safety profile is covered. The description adds value beyond that by disclosing return contents (author, title, summary, likes) and Error Handling behavior (empty result notice, timeout notice) — genuinely useful behavioral context for an open-world scraper.

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?

Front-loads the one-line purpose, then uses labeled Args/Returns/Examples/Error Handling blocks that are easy to scan. Slightly verbose because Args and Returns restate schema-visible information, but nothing is wasted or buried.

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 no output schema, the description usefully summarizes the return fields, and it covers the empty/timeout failure modes. For a simple 3-param read tool this is close to complete; it only lacks guidance on paging behavior and how it relates to sibling solution/discussion 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?

Schema description coverage is 100%, so page and problemId are already fully documented in the schema; the description largely repeats them. It does restate the response_format default ('markdown' 默认), adding marginal emphasis but no new semantics. Baseline 3 applies.

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 verb and resource: 获取牛客网特定题目的社区题解列表 (get the community solution list for a specific problem). This is clearly distinct from sibling nowcoder_get_problem (problem statement) by naming the 'list of community solutions' resource. It stops short of explicitly contrasting with siblings, so 4 rather than 5.

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 is implied (fetch solutions for a given problem) and the Examples section shows concrete invocation shapes. However, there is no explicit when-to-use/when-not or routing against alternatives like nowcoder_get_problem or nowcoder_get_discussion, which is the key ambiguity for this family of tools.

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?

Annotations already declare readOnly, idempotent, non-destructive and openWorld behavior, so safety is covered. The description adds genuinely useful behavioral context beyond that: page-load timeouts, network failure handling, and the empty-result fallback, which tell the agent how failures manifest.

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?

Front-loaded one-line purpose followed by clearly labeled Args/Returns/Examples/Error Handling sections. The Args block duplicates the schema, which is mild waste, but overall structure is tight and scannable.

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?

There is no output schema, and the description compensates by describing the returned fields (ID, title, difficulty, pass rate, tags). Combined with the annotation coverage of safety behavior, an agent has enough to call this correctly, though sibling differentiation remains missing.

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 all four parameters, and the 'Args' block largely restates them. The examples do add some combinatorial meaning (e.g., keyword + response_format=json), but the difficulty scale and defaults are already in the schema, so this stays at the baseline.

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 verb (列出) and resource (牛客网 ACM/OJ 编程题目) plus the filtering dimensions (keyword, difficulty). However, it never differentiates itself from the sibling nowcoder_search or nowcoder_list_topic_problems, which an agent could easily confuse with this list operation.

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 is implied through the examples (browse all, filter by difficulty, keyword search with JSON), but there is no explicit when-to-use vs when-not guidance and no routing to the alternative tools. The agent must infer that this is the generic listing tool versus the topic-scoped or search siblings.

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?

Annotations already declare readOnly, idempotent, non-destructive behavior, so the bar is lower. The description adds genuinely new context: error behavior for missing topics and page-load timeouts, plus the returned fields (编号、标题、难度、通过率). This goes beyond what annotations convey.

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?

Front-loaded with the purpose, then Args/Returns/Examples/Error Handling sections that are easy to scan. It is somewhat repetitive, restating parameters and topicIds that already exist in the schema, which costs a little efficiency but not readability.

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 no output schema, the description carries return-value disclosure and does so (编号、标题、难度、通过率), and it covers the failure modes. The only gap is the absence of any explicit alternative-tool guidance for an agent choosing among seven siblings.

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

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

Schema coverage is 100%, so baseline is 3, but the description adds value by expanding the topicId catalogue to ten entries versus the schema's five and clarifying the markdown-vs-json tradeoff in the examples. Page semantics are already covered by 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 states a specific verb (获取) and resource (专题题目列表) and scopes it to a named topic, which implicitly separates it from the generic nowcoder_list_problems. It does not explicitly name a sibling for differentiation, but the topic-scoping makes the boundary inferable.

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 is implied by the topicId list and the two examples, so an agent can see this is for topic-scoped browsing. However, it never says when to prefer this over nowcoder_list_problems or nowcoder_search, nor does it give exclusions.

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?

Annotations already declare readOnly/idempotent/openWorld, and the description adds real behavioral context beyond them: timeout handling, network-failure messaging, and the no-results suggestion. This is meaningful disclosure for a scraper-style tool that isn't captured by the annotations.

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?

Purpose is front-loaded in the first sentence, then organized into Args/Returns/Examples/Error Handling sections. Slightly verbose, but each block carries distinct information and nothing is wasted.

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?

There is no output schema, and the description compensates by listing returned fields (标题、链接、摘要、作者、时间) plus error behavior. For a 4-param, single-required search tool this is complete enough to invoke correctly.

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

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

Schema description coverage is 100%, with enums and descriptions already documenting every parameter including defaults. The description's Args block largely restates the schema; the examples add combination context but no new parameter syntax or constraints, so baseline 3 applies.

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 verb (搜索) and resource (牛客网内容) and enumerates the content types it can search (讨论帖、面经、编程题、职位). This distinguishes it from the narrower siblings like nowcoder_get_problem and nowcoder_list_problems, though it never names them 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?

Usage is conveyed only implicitly through the examples (Java面经 → discuss, 二叉树 → problem), which shows how the type filter maps to intent. There is no explicit statement of when to prefer this search tool over the more specific get/list siblings, nor any exclusion guidance.

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