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

无注释，描述需承担行为透明责任。提到了'相同答案不会重复提交'（幂等性）和'不支持代答权限审批'（权限限制），但未说明副作用、所需权限、错误行为等关键信息。对于回答操作，缺少对变更的透明披露。

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?

三句话，简洁且信息密集，没有冗余。但结构上可考虑将参数用法与行为限制分开，但总体可读。

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?

对于简单工具，描述提供了基本功能、参数用法和限制，但缺少参数alaias和questionId的说明，也没有输出或错误信息。在无注释和输出schema的情况下，信息尚不完整，但基本可用。

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覆盖率为0%，描述必须补偿。它解释了'selected'和'custom'的用法（精确标签和文字回答），但未说明'alias'和'questionId'的含义。虽然部分参数被解释，但关键参数仍不清晰。

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?

描述明确说明工具用于'回答指定的 DSH 普通问题'，动词和资源清晰。但'DSH 普通问题'含义模糊，且未与同级工具（如 talk_questions、talk_read）明确区分，不过整体目的明确。

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?

仅提到'不支持代答权限审批'，这是一个限制条件，但没有说明何时使用该工具、何时不使用，也未提及替代方案。缺乏使用场景指导。

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 burden. It does disclose a meaningful side-effect: the tool does not send messages ('不发送消息'). However, it does not explain overwrite behavior for an existing alias, idempotency, persistence, or error handling when the session does not exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no filler. The primary action is front-loaded, followed by a usage note and a valuable negative disambiguation. Every sentence 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?

For a simple bind action, the core invocation context is present. But with no annotations, no output schema, and 0% per-parameter schema descriptions, the description omits return behavior, alias-collision semantics, and error conditions. It is adequate but has clear gaps.

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 does: '对话' maps to sessionId, '目录' maps to cwd, '固定别名' maps to alias, and 'Codex/Claude' connects to the app enum. However, the enum value 'dsh' is unexplained, and the source/format of sessionId and cwd are not specified.

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 ('bind'), names the resources ('existing conversation' and 'directory'), and the target ('fixed alias'). It also distinguishes the tool from siblings: '不发送消息' separates it from talk_send, and '已有对话' differentiates it from talk_create.

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 a concrete trigger: use the tool to bind the Codex/Claude conversation that initiated the current task. It does not explicitly name alternatives or state when not to use the tool, but it provides clear enough context for an agent to decide.

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 discloses side effects (binding the current Codex/Claude conversation), default behavior (autoReturn=true and replyTo auto-filled), error handling (missing target causes error, not silent disable), reuse semantics (same alias/ID reuse the same conversation), and the fact that no task is dispatched until talk_send. This is comprehensive and 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 dense paragraph that front-loads the core purpose and then logically covers workspace selection, auto-return, reuse, and task dispatch. Every sentence adds value; it is concise given the complexity. Slightly long but not 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 8 parameters, no output schema, and no annotations, the description covers the key behavioral aspects and parameter relationships. It does not describe the success return value (e.g., conversation ID), which could be useful, but the agent can likely infer it from the creation action and schema. Overall, it is sufficient 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 coverage is 0%, so the description must add meaning. It explains the semantics of workspaceName, cwd, autoReturn, replyTo, and alias, including their relationships and defaults. However, it omits details for app, title, and requestId, though these are either trivial (app is const dsh) or inferable (requestId is a UUID). The description compensates well for the most complex 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 clearly states it creates a DSH native conversation, using a specific verb ('创建' = create) and resource ('DSH 原生对话'). It distinguishes from siblings by explaining the workspace/cwd selection and the auto-return behavior that ties to talk_follow and talk_send, so an agent can tell it apart from related tools like talk_bind or talk_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 description explains when to use this tool (to create a conversation) and gives clear context on workspace vs cwd requirements and the auto-return default. It references talk_follow and talk_send, implying alternatives and when they are needed, though it does not explicitly enumerate all sibling exclusions. This is solid guidance without being exhaustive.

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 and uses it well: it discloses that pausing DSH stops the original client and cancels queued prompts, pausing desktop only pauses bridge delivery, active is required to resume, and completed closes the callback without archiving. This is valuable behavioral nuance beyond the schema.

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?

Three dense, front-loaded sentences. The first sentence states the core capability, and the next two add necessary edge-case details without redundancy. Every sentence 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?

Given only two required parameters, no output schema, and no annotations, the description covers the main behavioral outcomes and special cases (DSH vs desktop, active requirement, completion side effects). It does not explain what 'alias' refers to or describe error conditions, but for the tool's complexity it is largely 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 clarify parameters. It explains the meaning and effect of the state enum values (active, paused, completed) in context, but it does not define 'alias' at all. The description partially compensates for the missing schema descriptions but leaves one parameter ambiguous.

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 explicitly states the tool's functions: '暂停或恢复投递，或将审查通过的任务标记完成' (pause/resume delivery, or mark a review-approved task as completed). This uses specific verbs and a clear resource, and the dual nature (control delivery vs. mark complete) is distinct from sibling read/send/list 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 context on when to set active (to resume after the original client stops) and distinguishes between DSH and desktop conversation behavior, but it does not explicitly name alternative tools or state when not to use this tool. Usage is implied rather than directly contrasted with 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?

With no annotations provided, the description carries the full behavioral disclosure burden. It reveals that the tool starts ongoing message forwarding, waits when the receiving side is busy, requires explicit resumption after a pause, and depends on a live MCP process and original client. This goes well beyond the schema, though it omits details like return behavior or how pausing is triggered.

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 compact and front-loaded: it states the core function first, then adds the operational constraints in short, clear sentences. Every sentence contributes meaningful information with no filler.

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 annotation coverage, so the description must fully equip the agent to call the tool correctly. It explains behavior and runtime requirements but omits parameter semantics, return behavior, and how to stop or resume the follow state, leaving meaningful gaps for a 3-parameter 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%, and the description does not explicitly explain source, destination, or enabled. The terms '发起方' and '接收方' hint at the destination and receiving side, and '开启后' loosely maps to enabled, but the mapping is indirect and not sufficient for an agent to confidently construct arguments.

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 action: after being enabled, it relays DSH final replies, questions, abnormal endings, and user-intervention messages back to the initiating Codex/Claude conversation. This gives a clear verb, resource, and message scope, though it does not explicitly differentiate itself from sibling tools like talk_send or talk_read.

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 useful operational context: wait when the receiver is busy, explicitly resume after pausing, and keep an MCP process and the original client running. However, it never states when to choose this tool over alternatives or when not to use it, so the usage guidance is implied rather than explicit.

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 burden. It explains filtering behavior and app-specific differences, but does not explicitly state whether the operation is read-only, any permission requirements, or potential side effects. 'List' implies non-mutating, but it is not stated clearly.

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 compact and information-dense. It covers purpose, filtering, app-specific behavior, and what it does not do in a few sentences 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?

For a simple list tool with two parameters and no output schema, the description covers the essential semantics and behavior. Missing return format details, but the tool's purpose is clear and siblings handle other operations.

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 cwd as exact directory filtering and clarifies Claude/Codex behavior for the app parameter. However, the 'dsh' enum value is not explained, leaving some ambiguity for that parameter value.

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 tool lists conversations from original clients, distinguishing between Claude and Codex behaviors and specifying the cwd filter. It clearly separates from sibling tools like talk_bind and talk_read by noting it does not bind or resume.

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 context on when to use (listing conversations) and what it does not do (bind or resume), but does not explicitly name alternatives like talk_bind or talk_read. The exclusion of binding/resuming is implicit 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 burden and does a solid job: it defines status semantics ('queued', 'unknown/sending/held', 'observed') and imposes a behavioral rule ('不得重发'). It also signals read-only intent via '读取', though it does not cover authentication, rate limits, or output shape.

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 three short sentences, front-loads the core purpose, and then adds only the essential status interpretations. Every sentence earns its place with no redundant filler.

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 zero parameters, no annotations, and no output schema, the description covers the main return categories and their meanings. It could be more explicit about the output format or the meaning of '自动回传错误', but for a low-complexity status-reading tool it 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?

The tool has zero parameters, so there is no parameter burden on the description. The baseline of 4 applies because no parameter documentation is needed; the description instead focuses on what the returned statuses mean.

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 a specific verb and resource: '读取近期回执、自动回传错误和事件连接状态' (read recent receipts, automatic callback errors, and event connection status). This distinguishes talk_outbox from siblings like talk_send and talk_read by focusing on delivery status and receipts, though it does not explicitly name a sibling for contrast.

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 actionable usage context: 'queued 表示排队中，可以等待；unknown/sending/held 不得重发' tells the agent when it is safe to wait and when resending is forbidden. It does not explicitly mention alternative tools, but the status-specific guidance gives clear operational direction.

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

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

With no annotations provided, the description carries the full burden. It implies a read-only operation via '读取' but does not explicitly declare non-destructiveness. It does note that permission approvals cannot be handled here, which is a useful limitation. However, it omits any description of return format, pagination, or side effects, leaving the agent partially in the dark.

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 three short sentences that are front-loaded with the core purpose. Every sentence contributes to understanding the tool's role and constraints, 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?

The tool is simple (one parameter, no output schema), but the description fails to explain the parameter and does not describe what the returned data looks like or how to distinguish questions from permission requests. While it gives some follow-up actions, the missing parameter semantics and output details make it incomplete 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?

The only parameter 'alias' is required but completely unexplained. The schema provides only a pattern with no semantic hint, and the description never mentions the parameter. With 0% schema description coverage and no compensation in the description, the agent cannot infer what alias refers to (e.g., a workspace alias, a question ID).

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 verb (读取/read) and the resource (DSH 的普通问题和权限请求 – regular questions and permission requests). It distinguishes the tool from talk_answer (which answers questions) but does not explicitly contrast it with the generic talk_read sibling, so sibling differentiation is incomplete.

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 offers some follow-up guidance: normal questions can be answered with talk_answer, and permission approvals must be handled in DSH Web. However, it does not state when to use this tool instead of talk_read or other read tools, nor does it provide explicit exclusions or selection criteria.

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 so excellently. It explains the meaning of returnRoute, lastReturn, held, paused, truncated, and idle, and explicitly warns against common misinterpretations: held does not mean return is disabled, and idle does not mean review passed. This prevents dangerous errors.

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 dense but every clause contributes meaning about a state or field. It could be slightly more readable with bullet points, but there is 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?

Since there is no output schema, the description rightly explains many return-field semantics and edge cases. However, it completely omits the meaning of the sole input parameter, alias, and does not describe the overall response structure. An agent can interpret results but may not know how to target the correct resource.

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 only required parameter, alias, is never mentioned in the description. Schema coverage is 0%, so the description provides no meaning for what alias identifies, what values are valid beyond the regex, or how it relates to the workspace/list context. This is a major 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 opens with a specific verb ('读取') and identifies a clear resource set: original client state, recent progress, final reply, user messages, and questions. This clearly marks it as a read/status tool distinct from write-oriented siblings like talk_send or talk_create, though it never explicitly names a sibling for 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?

The description provides actionable interpretive rules: 'held' means the recipient is holding the message and it must not be resent; 'paused' requires explicit recovery; 'idle' does not mean approval. These are strong when-not/conditional behaviors, but the description does not state when to choose talk_read over alternatives such as talk_list or talk_follow.

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 explicitly states that the same requestId will not be sent repeatedly (idempotency), that messages are persistently queued when the receiver is busy/unavailable, that it never resends when the result is uncertain, and that files remain local. These are important side-effect and reliability traits that help the agent anticipate 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?

The description is four short sentences, front-loaded with the primary action and then key behavioral guarantees. Each sentence adds value—no redundant or vague content. It is appropriately sized for a tool with this complexity.

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

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

Given the tool's moderate complexity (4 params, no output schema, no annotations), the description covers the core behavior, idempotency, queuing, retry policy, and file locality. It implies the prerequisite of binding but does not explicitly state what happens if the conversation is not bound or how errors are surfaced. Overall, it is fairly complete but could explicitly mention the binding prerequisite.

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 clarifies that 'prompt' and 'files' are the content sent, and that 'requestId' serves as an idempotency key. However, it does not explain the 'destination' parameter beyond implying it is the bound conversation, and it does not detail constraints like max file count or prompt length (though these are in the schema). Partial compensation is 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 states the action: sending prompts and local file paths to a bound conversation. This distinguishes it from sibling tools like talk_read, talk_list, and talk_create, which are read/list/create operations. The verb 'send' and resource 'bound conversation' are explicit and specific.

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 context by requiring a 'bound conversation' (已绑定的对话), suggesting a prerequisite to bind first. However, it does not explicitly state when to use this tool versus alternatives like talk_outbox or talk_delivery_control, nor does it provide exclusions. The idempotency and queuing behavior give operational guidance but not selection criteria.

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 explicitly declares '只读，不创建或重命名工作区' (read-only, does not create or rename), which is a critical safety trait. It also specifies the output content ('精确名称和目录' – exact names and directories), offering meaningful behavioral context beyond the empty schema.

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 three short, focused sentences: the first states the primary function, the second clarifies read-only/non-mutating behavior, and the third connects the tool to its intended downstream use. No redundant words; each sentence earns its place 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 0-parameter read-only list tool with no output schema, the description covers what the tool does, what it returns (names and directories), and when to use it (before talk_create). It does not mention pagination, error conditions, or authentication, but these gaps are minor given the tool's low complexity.

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 there is no parameter semantics to explain. The baseline for 0-parameter tools is 4; the description appropriately omits parameter details since none exist, and no additional compensation is required.

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: '列出已有 DSH 工作区的精确名称和目录' (list exact names and directories of existing DSH workspaces). It also explicitly distinguishes from mutation tools by stating '只读，不创建或重命名工作区' (read-only, does not create or rename workspaces), making the purpose unambiguous.

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 concrete usage scenario: '在 talk_create 中使用 workspaceName 选择工作区' (use workspaceName in talk_create to select a workspace), telling the agent when to call this tool. It also implies not to use it for creation/renaming via the read-only statement, though it does not explicitly name alternative sibling tools (e.g., talk_list).

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