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

No annotations provided, so description carries full burden. Discloses authorization requirement (PM only) and scope behavior. However, lacks details on post-approval actions (e.g., whether the blocked call is automatically re-executed or requires manual retry), and no mention of logging or 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?

Two concise sentences in Chinese, front-loading purpose then explaining scope. No unnecessary words; every sentence is informative.

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?

Covers core functionality and parameter usage adequately. However, does not describe what happens after approval (e.g., automatic execution of the blocked call), nor how to obtain session_id or approval_id in typical use. Given no output schema, these gaps reduce completeness.

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%, but description adds value by explaining scope semantics ('once' vs 'session') and the source of block_id ('from poll_session or watch_result blocks'). This provides context beyond the schema definitions.

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 purpose: 'allow tool calls blocked by policy (PM only)', with specific verb '放行' and resource '被策略阻断的工具调用'. It distinguishes from sibling 'deny_tool' by being the approval counterpart.

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?

Explicitly states 'PM only', providing clear use context. Explains two scope options (once/session) and their effects. Does not explicitly mention alternatives, but sibling 'deny_tool' implies contrast.

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 effectively communicates key behavior: the tool is non-blocking ('send and return immediately') and requires polling via poll_session for progress tracking. This adequately informs the agent of the tool's async nature, though it could detail error handling or response structure.

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

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

The description is concise with two efficient sentences, front-loading the primary action and then directing to the tracking counterpart. Every sentence serves a purpose with no 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?

Given 5 parameters, complete schema descriptions, and no output schema, the description covers the core usage pattern (send, poll). It lacks details about return format or error states, but the essential context for using the tool correctly is present.

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 tool description adds no additional semantics beyond the schema descriptions, which already define each parameter. No improvement or degradation.

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: sending a task to a specified session and returning immediately. It uses a specific verb ('send'), clearly identifies the resource ('task' to 'session'), and distinguishes from sibling tools like poll_session by directing progress tracking there.

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 clear guidance: use this tool to initiate a task and then poll with poll_session for progress. It implies a fire-and-forget pattern, which helps the agent decide when to use this vs. other tools like watch_session or poll_session directly. However, it could be more explicit about when not to use it.

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. It discloses that the tool checks, may submit, and may start a new watch, but lacks details on side effects (e.g., old watch status), prerequisites, error handling, or authorization needs. Some behavioral context is provided but not comprehensive.

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 sentence that is efficient and front-loaded, but it is somewhat dense with multiple clauses. Could be more concise by splitting into simpler sentences, but overall 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?

The description explains the tool's role in an automation loop, which is helpful. However, it does not mention the return value, error states, or what happens if the session is not completed. Given the lack of output schema and annotations, more detail would be beneficial for full understanding.

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 baseline is 3. The description adds context about how the parameters are used in the automation loop (e.g., 'watch_id' for current watch, 'next_instruction' triggers automatic submission), but does not substantially extend beyond what is already 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 clearly states the tool checks background monitoring results and automatically submits the next instruction and starts a new watch if the session is completed. It provides a specific verb and resource, but does not explicitly differentiate from sibling tools like 'watch_session' or 'get_watch_result', which could cause confusion about when to use each.

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: after a task session is completed, to continue automation. However, there is no explicit guidance on when not to use this tool or what alternatives exist. The description relies on context to infer appropriateness.

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

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

No annotations provided, so description must cover behavior. It lists the four decisions but does not elaborate on side effects (e.g., whether retry re-executes from scratch, whether abort is irreversible). The schema enum descriptions add some detail but not comprehensive behavioral 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?

Two concise sentences that front-load the purpose and use case. No unnecessary words, every sentence adds value.

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 no output schema and 3 well-documented parameters, the description covers the main functionality. However, it could be more complete by hinting at the outcome of each decision after use.

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 baseline is 3. The description adds minimal extra information beyond the schema. The phrase '用自定义指令覆盖' aligns with the manual decision but does not significantly enhance understanding.

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 the tool's purpose: make decisions on paused workflows (retry, skip, abort, manual override). This distinguishes it clearly from sibling tools like execute_workflow (start new) or approve_tool (approvals).

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?

Description indicates usage when workflow is paused/blocked. While it doesn't explicitly mention when not to use or provide alternatives, the context of sibling tools makes it clear. A minor gap for explicit 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?

No annotations are provided, so the description carries full burden. It mentions parameter specification but omits behavioral traits like side effects, prerequisites, or return value. The schema covers input, but behavioral context is minimal.

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 concise sentence that delivers the core purpose upfront. Every word is necessary, with no wasted text.

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 and no output schema, the description provides insufficient context. It does not explain the concept of 'Kimi Code session', lifecycle, or how to interact with the created session, which is essential given the array of 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?

Schema coverage is 100%, so baseline is 3. The description highlights two key parameters (cwd and permission_mode) but adds no new semantics beyond what the schema already 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 clearly states the verb 'create' and the resource 'new Kimi Code session', specifying the main action. It distinguishes from sibling tools like 'chat_with_session' by indicating it initiates a new session.

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 does not provide explicit when-to-use or when-not-to-use guidance. While the name implies creation, no alternatives or exclusions are mentioned, leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries full burden. It does not disclose effects of denial (e.g., whether it terminates the session, logs, or is reversible), rate limits, or authorization beyond PM.

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 concise (one sentence) and front-loaded with the core action. It could benefit from slightly more structure but 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?

For a denial tool with 3 parameters and no output schema, the description lacks details on how to use each parameter in context, what the return value is, and the overall flow. This is insufficient for an agent to use reliably.

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% with adequate parameter descriptions. The tool description adds no extra parameter details, so 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 denies blocked or pending-approval tool calls, with a specific audience (PM only). It distinguishes from the sibling approve_tool by focusing on denial.

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 that the tool is for PM use and applies to blocked or pending-approval calls, but does not explicitly contrast with approve_tool or provide when-not-to-use scenarios.

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 discloses key behaviors: it excludes thinking by default to save tokens, returns immediately regardless of the wait parameter, and communicates via REST API. It lacks details on error handling or side effects, but covers the main behavioral traits.

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

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

The description is concise with four front-loaded sentences. Each sentence adds meaningful information: purpose, communication method, default behavior, and usage tip for thinking content. No 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?

Given no output schema, the description should hint at the return value, but it does not. It also does not explain error scenarios. While it covers core functionality and polling guidance, it lacks completeness for a tool with 8 parameters and 2 required fields.

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 parameters are already documented. The description adds value by explaining default behavior (exclude thinking) and giving a use-case for include_thinking (when replies are vague), going beyond the schema descriptions.

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

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

The description clearly states the tool's purpose: sending a prompt to a target session and waiting for a reply. It specifies the communication method (Kimi Server REST API) and distinguishes itself from sibling tools like poll_session by noting that it returns immediately due to MCP timeout.

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 context for when to include thinking content (when replies are vague) and explains the deprecated wait parameter, advising to use poll_session for progress. However, it does not explicitly state when not to use this tool or list all 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?

The description discloses key behaviors: loading template, creating session, adaptive adjustment, pausing when blocked. But with no annotations, more details (e.g., side effects, permissions) would improve 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?

Single sentence covers the main workflow steps efficiently, though it could be structured into clearer bullet points.

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 8 parameters and no output schema or annotations, the description covers the core flow but lacks usage guidelines and deeper behavioral details for a complex tool.

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

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

Schema coverage is 100%, so descriptions already explain parameters. The description only adds context for template_name (mentioning list_templates). 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 executes a workflow template, loads it, creates a session, and issues instructions, distinguishing it from sibling tools like create_session or learn_workflow. However, 'adaptive adjustment' is vague.

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 on when to use this tool versus alternatives like run_flow or execute_prompt. Lacks context for prerequisites or 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?

No annotations are provided, so the description carries full burden. It lists returned fields but does not disclose that the tool is read-only, whether authentication is required, or any side effects. A 'get' tool should explicitly state its read-only nature.

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 concise sentence that covers the core purpose and return content. It is front-loaded and efficient, but could be slightly more structured with explicit read-only indication.

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 get tool with one parameter and no output schema, the description is adequate but not complete. It fails to mention error conditions, permission requirements, or that the tool is idempotent. Additional details would improve completeness.

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% with detailed parameter description for session_id. The tool description adds context about return fields but does not add significant meaning beyond the schema for the parameter itself. 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?

Description clearly states the tool retrieves detailed session info and lists specific fields (title, working directory, etc.). However, it does not distinguish itself from sibling tools like list_sessions or read_session_log, leaving the agent to infer the difference from the name alone.

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 no explicit guidance on when to use this tool versus alternatives. It implicitly suggests using it when session details are needed, and hints that session_id can be obtained from list_sessions, but lacks when-not or alternative tool recommendations.

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 indicates a read-only operation returning status metrics. It does not disclose potential side effects, latency, or freshness of data, but the fields imply no destructive actions.

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?

Single sentence front-loading the action and listing fields. Every word serves a purpose.

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

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

Given no output schema, the description adequately enumerates return fields. It covers the tool's function and outputs, though omits format or response structure 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?

No parameters exist, so baseline is 4. The description adds no param information since none is needed.

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 retrieves the current status of the debug tunnel, listing specific fields: connected clients, Wire protocol status, message queue length, and running time. This distinguishes it from sibling tools which have different purposes.

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 on when to use this tool versus alternatives. Does not mention prerequisites, caveats, or scenarios where it should be avoided.

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. It mentions the asynchronous nature (awaiting result) and the null return while waiting, but does not disclose whether the tool is idempotent, if repeated calls are safe, or if there are any side effects. More behavioral context is needed.

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 main purpose and a key behavioral note. No redundant words; every sentence adds value.

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 low complexity (one parameter, no output schema), the description is minimally adequate. However, it could be more complete by mentioning that it is a non-blocking poll, the expected response format beyond null, or how it relates to other tools like set_watch_output.

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 one parameter with 100% coverage in its description. The tool description adds no extra meaning beyond what the schema already provides. Thus a baseline score of 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 it retrieves the result of a watch_session. The verb '获取' (get) and resource '后台监听结果' (background monitoring result) are specific. It does not explicitly differentiate from siblings like poll_session, but the pairing with watch_session is contextually evident.

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 indicates that null means still waiting, which implies it is meant to be called after watch_session. However, it does not provide explicit guidance on when to use this tool versus alternatives like poll_session, nor does it mention any prerequisites or conditions.

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 adds behavioral context via the sieve metaphor, indicating the grading is not absolute. However, it does not disclose whether the tool is read-only, requires authentication, or has rate limits, leaving some gaps.

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 concise: two sentences plus a metaphor, front-loading the purpose and adding nuance without unnecessary 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 simple tool with 3 parameters and no output schema, the description covers purpose and return type but does not specify the output structure or error handling. It is adequate but not fully 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 coverage is 100%, so baseline is 3. The description does not elaborate on parameter meanings beyond what the schema already provides, adding minimal 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 clearly states the tool performs LLM automatic scoring verification on task session output, returning pass/fail and detailed feedback. This is a specific verb-resource pair, though it does not explicitly distinguish from sibling tools like approve_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?

The description implies usage for grading session outputs and provides cautionary interpretation (pass != perfect, fail != real problem). However, it lacks explicit guidance on when to use this tool versus alternatives such as approve_tool or deny_tool.

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

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

No annotations provided, so description bears full burden. It fails to disclose side effects (e.g., file creation, storage location), permissions needed, or whether it modifies state. Only states the abstract purpose.

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?

Single sentence is concise and front-loads key purpose. However, it is in Chinese, which may be less accessible for some AI agents, and could be slightly more structured.

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?

Description is adequate but incomplete: fails to explain where the YAML template is saved, output details, or precedence rules among parameters (though schema covers these). With 6 parameters and no output schema, more context is needed.

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 3 applies. The description adds no extra parameter semantics beyond what the schema already provides (e.g., precedence of steps/description/from_session is in schema but not in description).

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 learns workflows from verbal descriptions or historical sessions and generates reusable YAML templates. This distinguishes it from sibling tools like execute_workflow, but explicit differentiation is missing.

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 (learning workflows), but lacks explicit when-not-to-use or alternative references. Given many sibling tools, exclusion guidance would be helpful.

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 transparently discloses the filtering behavior (only user prompts and assistant replies, removing tool calls, thinking, step_end). It does not discuss potential permissions or mutability, but as a listing operation, it is sufficiently transparent about its read-only data reduction.

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 concise, consisting of three sentences that front-load the main action (列出输入输出记录), explain the filtering behavior, and state the use case. Every sentence earns its place with no redundancy or 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?

While the description covers purpose, filtering, and use case, it lacks any mention of the output format or structure. Since there is no output schema, the description should ideally describe what the returned data looks like (e.g., array of objects with prompt and response). This gap reduces completeness for a tool with three parameters and no output 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?

All three parameters (session_id, limit, max_content_length) have descriptions in the input schema, providing adequate semantics. The overall description does not add parameter-specific information beyond the schema, so the baseline score of 3 is appropriate given 100% 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 states the tool lists input-output records of a session, specifically extracting only user prompts and assistant text replies while filtering out tool_call/thinking/step_end noise. It distinguishes from sibling tools like read_session_log by emphasizing noise reduction for quick conversation flow understanding.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear use case ('用于快速了解对话流程' - to quickly understand conversation flow). It implies when to use this tool but does not explicitly mention when not to use or name alternative sibling tools, though context from sibling names suggests differentiation.

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

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

No annotations provided. Description implies a read operation ('list'), which is sufficient for a simple list tool. However, it does not explicitly state safety, auth needs, or side effects. Minimal additional behavioral context beyond the action.

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 concise sentences front-loading the main action and adding key detail (built-in vs custom, verification status). 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?

Given no output schema and no annotations, the description adequately explains what the tool returns (policy types and verification status). Missing details like ordering or pagination, but for a zero-parameter list tool, it is mostly 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?

No parameters exist, and schema coverage is 100%. Baseline 3 as per rule. Description adds no parameter-specific meaning but clarifies the output scope (built-in vs custom policies), which is mildly helpful.

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 the tool lists all available permission policies, including built-in and custom types, with verification status. Differentiates from sibling list tools (e.g., list_sessions) by specifying resource type.

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 explicit usage guidelines or when-not-to-use. Implies usage for listing policies, but does not name alternatives or exclusions. Adequate but not informative.

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 burden of behavioral disclosure. It accurately describes a read operation (listing) and the output structure. It does not mention side effects, but for a list operation, transparency is adequate.

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

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

The description is a single concise sentence that efficiently conveys purpose, output fields, and sorting order. Every part is necessary and well-structured.

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 listing tool with one optional parameter and no output schema, the description is complete: it states what it lists, the fields returned, and the sort order. No critical gaps exist.

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% for the single parameter 'limit', so baseline is 3. The description does not add extra meaning or context beyond the schema, which already specifies default, min, max, and description.

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 '列出' (list), the resource '所有 Kimi Code CLI session' (all sessions), and the scope. It distinguishes from siblings like create_session and get_session_info by focusing on listing all sessions with specific fields.

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 for obtaining a list of all sessions but does not explicitly mention when to use or when not to use, nor does it reference alternative tools like get_session_info for details. Usage is implied but not guided.

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 that the tool returns specific fields (name, version, steps, description), but does not mention authentication requirements, side effects, or potential pagination. Some behavioral context is given, but it is not comprehensive.

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 concise with two sentences. It front-loads the main action and includes only essential information, 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?

Given the tool's simplicity (no parameters, no output schema, no annotations), the description covers the basic purpose and return values. However, it lacks context about authentication, ordering, or potential limitations, which would make it more complete. Still sufficient for a straightforward list operation.

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 and the schema coverage is 100% (empty schema). The description correctly implies no arguments are needed, which aligns with the schema. Per scoring guidelines, zero parameters earns a baseline of 4, and the description adds no unnecessary information.

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 lists all available workflow templates and specifies the returned fields (name, version, number of steps, description). It effectively distinguishes this tool from sibling tools like list_sessions (sessions) and list_io_records (records) by targeting workflow templates specifically.

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 use when needing a list of workflow templates, but provides no explicit guidance on when not to use it or how it compares to alternatives. No exclusion criteria or alternative tools are mentioned.

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 full burden. It discloses the main action (archival from L2 to L1) but lacks details on side effects (e.g., whether L2 findings are deleted), permissions needed, or idempotency. Adequate but could be more 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 short sentence that conveys the core purpose efficiently. No wasted words, and it 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?

Given no output schema and no annotations, the description is minimal. It does not explain what L2 findings vs L1 learnings entail or the exact archival semantics. Adequate for a simple tool but lacks depth for a complex domain.

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 describes all parameters. The description adds no extra meaning beyond the schema, so a baseline of 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 archives L2 findings from a session into L1 learnings, specifying the direction (L2 to L1) and a precondition (PM review). This distinguishes it from generic memory operations like memory_set or memory_delete.

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 includes a usage condition ('PM 审查后调用' meaning 'call after PM review'), providing clear context. It does not explicitly mention when not to use or alternatives, but 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, the description must disclose behavioral traits. It only notes permission requirements (destructive nature implied but not stated). It lacks information about effects on success/failure, whether the operation is permanent, or any side effects, which is critical for a deletion 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 a single sentence, concise and to the point. It could be slightly more structured or front-loaded with critical info, but it is not verbose.

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

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

Given no output schema and no annotations, the description is incomplete. It does not explain the irreversible nature of deletion, error handling, or what happens to related data. For a potentially destructive tool, more context is needed.

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 covers all three parameters with descriptions (100% coverage). The tool description adds no additional meaning to the parameters, so the baseline score of 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 action (delete) and the resource (key). It is specific enough to understand the core function, but it does not differentiate from sibling tools like memory_archive, which might serve a similar 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 mentions who is authorized to use the tool (PM or writer), providing a usage constraint. However, it does not specify when to use this tool versus alternatives like memory_set or memory_archive, nor does it include any exclusions or context for appropriate use.

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

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

No annotations provided, so description carries full burden. It explicitly states read operation (读取) and discloses key behaviors: returns all entries if key omitted, supports expired filtering. No mention of performance or auth, but sufficient for a read 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?

Two succinct sentences with no extraneous information. Action is front-loaded ('读取指定命名空间下的条目'), and key variations are covered efficiently.

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 tool with 4 parameters and no output schema, the description omits the return format (e.g., single JSON object, list). It adequately covers input behavior but leaves the output structure unspecified, which an agent might need.

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% with descriptions for each parameter. The description adds practical context: omitting key returns all entries, and the include_expired parameter enables filtering. This enriches understanding beyond the schema alone.

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 it reads entries under a namespace, and describes key behaviors (all entries vs specific, expired filtering). However, it does not differentiate from similar sibling tools like memory_list, though the 'get' vs 'list' distinction is implied.

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?

Description implies when to use (to read entries) and mentions the include_expired parameter, but lacks explicit guidance on when not to use it or alternatives. Sibling tools like memory_set or memory_delete suggest different purposes, but no direct comparison.

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

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

No annotations provided, so the description carries the burden. It discloses the tool lists keys without values and supports prefix matching, but lacks details on pagination, limits, or error handling. It does not contradict 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?

Two concise sentences with no waste. The purpose is front-loaded, and every sentence adds valuable information.

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 operation with two optional parameters and no output schema, the description is fairly complete. It explains return type (keys only), parameter usage, and omission behavior. Minor gaps: no mention of rate limits or result limits.

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% and both parameters have descriptions. The description adds context: project is an absolute path, namespace is a prefix, and omitting parameters lists all namespaces. This adds value 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?

The description clearly states the tool lists key names under a specified namespace without values, and mentions prefix matching and the effect of omitting parameters. It distinguishes from siblings like memory_get (which returns values) and memory_delete.

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 guidance on prefix matching and how omitting parameters lists all namespaces. It implies when to use different parameters but does not explicitly state when not to use the tool or compare to 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?

With no annotations, the description carries full burden. It discloses upsert behavior, version increment, and automatic recording of write time and source session. However, it does not discuss side effects like potential size limits or permission requirements.

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

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

The description is a single sentence that is front-loaded and concise, covering the essential behavior without unnecessary 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 set tool with 6 parameters and no output schema, the description covers the main action and upsert behavior. It lacks details on version semantics and expiration implications, but is reasonably 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 coverage is 100% with each parameter described. The description adds overall context but does not provide additional meaning beyond the schema. Baseline 3 is appropriate given schema richness.

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 writes a key-value pair to a namespace with upsert behavior and version increment. It distinguishes itself from sibling tools like memory_get (read) and memory_list (list) by being the write 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?

The description implies usage for storing data, but does not explicitly state when to use or when to avoid. It lacks exclusion criteria or alternatives, though the context of sibling tools provides some 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?

Since no annotations are provided, the description carries full responsibility. It clearly states the kinds of information returned, indicating a read-only query. No side effects are mentioned, and the description is consistent with the tool's name. Could be improved by noting that it does not modify data.

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 lists all relevant output items without unnecessary words. It is well-structured and front-loaded with the core action.

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 low complexity (one optional parameter, simple output), the description is fully adequate. It covers the tool's scope and output content comprehensively, despite the absence of an output 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 100% for the single parameter 'project', so the baseline is 3. The tool description does not add extra semantic meaning beyond what the schema already provides (absolute path, optional, defaults to current project).

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 purpose: viewing the overall status of the project knowledge base, listing specific metrics (entry count, last update, expired entries, namespace distribution). It distinguishes itself from sibling tools like memory_list and memory_get, which focus on individual entries or lists, not aggregated status.

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 for checking aggregated knowledge base status, but does not explicitly state when to use this tool versus alternatives such as memory_list or memory_get. It provides context about the optional project parameter but lacks direct guidance on 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?

In the absence of annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool preferentially uses WebSocket push cache for zero I/O, indicating it is a lightweight read operation. This transparency about caching and efficiency adds value beyond the basic purpose.

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 sentence that concisely conveys the action, resource, output, and behavioral trait. Every word earns its place; there is no fluff 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 simple tool with one parameter and no output schema, the description provides sufficient context: it states what it does, what it returns (structured status report), and how it operates (caching). It could be more detailed about the report structure, but overall it is adequate.

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 provides a description for the single required parameter (session_id), and the description does not add any additional meaning or usage context for the parameter. With 100% schema description coverage, the baseline score of 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 that the tool polls session running status and returns a structured status report. It uses a specific verb ('poll') and identifies the resource. It implicitly distinguishes from siblings like 'watch_session' and 'get_session_info' by focusing on polling and caching.

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 for polling session status efficiently via WebSocket cache, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'watch_session', 'get_session_info'). No when-not-to-use or exclusion criteria are given.

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?

Only annotations missing; description enumerates returned fields but does not disclose that it's read-only, side effects, or permissions. Adequate but not extra.

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 sentences, concise and front-loaded with purpose. Could be structured slightly better but overall 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?

Given no output schema and 5 parameters, description provides sufficient context about purpose and return values, though could mention output format hints.

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 3 is appropriate. Description adds no additional parameter meaning beyond what 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?

Description clearly states it reads session conversation logs, lists specific returned fields, and identifies use case in multi-turn orchestration, which distinguishes it from siblings like poll_session.

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?

Explicitly says '用于多轮编排时检测目标 session 的处理状态' providing clear usage context, but does not specify when not to use or offer 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?

With no annotations, the description must disclose all behavioral traits. It explains the asynchronous immediate response and polling mechanism, but fails to mention error handling, statefulness, or destructive potential. The lack of annotations places a heavier burden that is not fully met.

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 sentences long, with each sentence serving a distinct purpose: defining the tool, explaining the workflow, and describing the response behavior. It is front-loaded and contains no redundant information.

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 complexity (8 parameters, no output schema), the description covers the high-level execution flow but lacks details on return values, error scenarios, and required parameters. It hints at response behavior but does not fully equip an agent to understand the tool's complete behavior.

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

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

Schema coverage is 100%, so all parameters have descriptions. The tool description adds context about step progression and session creation but does not elaborate on individual parameters beyond what the schema provides. Thus, it meets the baseline without adding significant extra semantic 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 clearly states it's a step-by-step flow execution engine that creates sessions and submits tasks progressively, with automatic progression and tracking via poll_session. This distinguishes it from siblings like 'execute_workflow' or 'create_session' by emphasizing sequential step execution and polling.

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 for multi-step workflows where steps are executed sequentially and automatically, and tracks progress via poll_session. Though no explicit 'when not to use' or alternatives are given, the context is clear enough for an agent to decide to use this tool for step-by-step execution.

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 disclose behavior. It states that results are automatically written to the file on prompt.completed, which is useful. However, it does not mention whether the file is overwritten or appended, nor the required permissions or error handling.

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

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

The description is a single sentence in Chinese, concise and front-loaded with the main action. Every word provides value, and there is no redundancy.

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

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

Given no output schema, the description should explain return values, which it does not. It adequately describes the setup behavior but lacks details on success/failure outcomes or side effects. It is moderately complete for a simple setter.

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 the schema already describes the 'path' parameter as an absolute path with an example. The description adds no additional parameter information beyond the schema, so a baseline of 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 uses a specific verb ('设置' - set) and a clear resource ('监听结果文件路径' - watch result file path). It also explains the effect (automatic writing on prompt.completed), distinguishing it from siblings like 'get_watch_result' which are getters.

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 clear context: use it to set the path for automatic writing after prompt.completed. While it doesn't explicitly state when not to use, the context implies it should be used before watching, and siblings like 'get_watch_result' suggest alternatives for reading.

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 disclose behavior. It mentions WebSocket and real-time delivery but omits critical details: error handling, prerequisites (client connection), rate limits, or side effects. This is insufficient for an agent to fully understand operational consequences.

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 concise: two sentences front-load the primary purpose and mechanism. Every word adds value with no redundancy.

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

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

Given the simplicity of parameters and lack of output schema/annotations, the description is incomplete. Missing: prerequisites (client connection), error scenarios, behavior when no clients are connected, and any additional constraints. A more thorough description is needed for safe 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 100% with two parameters described. The description adds no additional meaning beyond the schema; it does not clarify the nature of 'content' or the purpose of 'in_reply_to'. Baseline score of 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?

Description clearly identifies the tool's function: real-time push of processing results to connected debugging clients via WebSocket. It distinguishes from polling by stating '无需轮询', but does not explicitly name sibling tools like 'poll_session'.

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?

Implied usage scenario: real-time streaming is preferable to polling. However, no explicit when-to-use or when-not-to-use guidance is provided, and no alternatives are mentioned despite the presence of 'poll_session' in sibling 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?

With no annotations provided, the description carries the full burden. It mentions background listening and WebSocket waiting, but lacks details on destructive behavior, authentication, or error states. Adequate but not thorough.

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 sentences provide essential information with no wasted words. The description is front-loaded with purpose and usage, making it easy to parse.

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 tool with one parameter and no output schema, the description covers purpose, usage context, and next steps. Some details like failure handling are missing, but overall it is complete enough for a basic monitoring tool.

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

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

Schema coverage is 100% with a clear parameter description. The tool description does not add extra meaning beyond what the schema provides, so 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 starts a background listening task for session completion status, explicitly distinguishes from siblings like poll_session (polling) and get_watch_result (retrieving results), and specifies when to call it.

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 indicates when to use (after submitting a task) and what to do after (use get_watch_result), providing good context. It does not explicitly mention when not to use, but the guidance is sufficient for correct invocation.

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