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

With no annotations provided, the description carries the full burden. It discloses the async execution mode, which is a key behavioral trait, but does not explain consequences like needing to poll for results or handling partial failures.

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, front-loaded sentence with no filler. It is concise but arguably too terse given the complexity of the tool; still, it earns a 4 for efficiency.

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 of parallel dispatch and async execution, the description is incomplete. It does not mention what the tool returns (e.g., task IDs), how to retrieve results, or error handling behavior, and there is no output schema to fill the gap.

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 description adds no parameter-level detail beyond what the schema provides. While the schema covers the top-level 'tasks' parameter, nested fields like max_turns, allowed_tools, system_prompt, and working_directory lack descriptions and the tool description does not compensate.

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 dispatches multiple tasks in parallel to different Claude CLI subagents, clearly distinguishing it from single-task siblings like dispatch_task. It is a specific verb+resource description.

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

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

No guidance is provided on when to use this tool versus alternatives such as dispatch_task. The description does not mention conditions, 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 the full behavioral burden. It does disclose a key behavioral trait beyond the schema: sync blocks until completion and returns results, while async returns immediately with a task_id. However, it omits side effects, failure modes, resource implications of spawning a CLI subagent, and how the async result is later retrieved — meaningful gaps for a zero-annotation 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 sentences, no filler: the first establishes the verb+resource, the second front-loads the two execution modes with their consequences. Every clause earns its place, and the most decision-relevant information (sync vs. async behavior) is placed immediately after the purpose statement.

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 7-parameter tool the schema covers parameter semantics fully, and the description covers the core execution behavior. But with no output schema and no annotations, the description should explain the return shape of sync results and the async follow-up flow (e.g., that async task_id can be queried via get_task_status/get_task_result). These omissions leave an agent guessing about the post-dispatch workflow.

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

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

Schema description coverage is 100%, so the schema already documents all 7 parameters and the baseline is 3. The description adds some value by tying 'mode' to concrete behavioral outcomes (sync returns results, async returns task_id), which the schema's '执行模式，默认 sync' does not, but it adds nothing about the other six parameters. Adequate but not compensating-driven.

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

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

Description states a specific verb+resource: '派发任务给 Claude CLI 子代理' (dispatch tasks to Claude CLI subagents), and adds a concrete behavioral distinction between sync (wait for results) and async (background, immediate task_id). This is clear enough to separate it from status/result/list/stop siblings by verb alone, but it never explicitly names a sibling or the case it is not (e.g., dispatch_parallel), so it stops short of a 5.

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

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

The description gives explicit mode-level guidance: choose sync when you want to wait and receive results, async for background execution with immediate task_id. However, there is no tool-level guidance versus alternatives — notably dispatch_parallel, which is the most confusable sibling — and no exclusions or prerequisites (e.g., that async tasks should later be polled via get_task_status/get_task_result). Usage is implied rather than fully routed.

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 disclosing behavior. It does explain the main conditional behavior (completed vs running), but it omits details about wait semantics, error cases, and what 'current status' includes. It is not misleading, 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 two short sentences with no filler. The primary action is front-loaded, and the conditional behavior is stated in the second sentence 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 simple two-parameter tool with full schema coverage, the description plus schema is mostly sufficient. A minor gap is that the return format of the final result or status is not described, but the core calling requirements are covered.

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% because both task_id and wait have descriptions in the input schema. The tool description itself adds no parameter meaning beyond what the schema already provides, 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 tool retrieves the final result of a completed task, and it adds the conditional behavior of returning current status if the task is still running. It is specific about the resource (task result) but does not explicitly differentiate itself from the sibling get_task_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 conditional phrase '如果任务仍在运行，返回当前状态' implies when the tool is useful, but there is no explicit guidance about when to prefer get_task_status or when waiting is appropriate. Usage context is implied rather than clearly stated.

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?

There are no annotations, so the description carries the full burden. It does indicate a read-style behavior ('查询') and discloses the output (status and recent logs), but it does not mention error behavior, log size limits, or whether any side effects occur.

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, front-loaded sentence with no filler. Every word contributes to defining the tool's 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?

For a simple read tool with two well-documented parameters, the description is minimally adequate. However, without annotations or an output schema, it could have clarified what status values are returned and how logs are formatted, and it gives no usage context relative to 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 description coverage is 100%, so the schema already documents both task_id and include_logs. The description adds no additional meaning about parameter formats, defaults, or how include_logs affects output.

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 '查询' (query) and names the exact resource ('指定任务' / specified task) and what it returns (current status and recent logs). It is clear, though it does not explicitly contrast itself with siblings like get_task_result or list_tasks.

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

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

No guidance is given about when to use this tool versus siblings such as get_task_result, list_tasks, or dispatch_task. The description states only what the tool does, leaving the agent to infer appropriate usage.

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 behavioral burden, yet it only states that the tool lists tasks. It does not disclose whether the result is paginated, ordered, read-only, or shaped in any particular way, nor does it mention potential side effects or absence thereof.

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, focused sentence with no filler. The key scope ('all tasks managed by this MCP Server') is front-loaded, making it immediately clear what the tool does.

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

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

The tool is simple with only one optional parameter, so the description is nearly sufficient arbiter for basic invocation. However, it omits any mention of the optional status filter, output shape, or how this tool relates to get_task_status, leaving the agent to infer context from the schema and sibling names.

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%: the status_filter parameter already has an enum and a clear description with default value. The tool description adds no extra meaning about the filter, so it neither helps nor hurts 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 uses a specific verb, '列出' (list), and a clear resource: '所有由本 MCP Server 管理的任务' (all tasks managed by this MCP Server). It clearly indicates a collection-level listing operation and is easily distinguished from sibling tools like get_task_status, which target individual tasks.

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 guidance on when to use this tool versus alternatives such as get_task_status or dispatch_task. There is no explicit 'use this when...' context, no exclusions, and no mention of which sibling tool to prefer for single-task lookups.

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 running tasks are stopped before resuming, a critical side effect. It does not cover other states (e.g., failed) or potential errors, but the disclosed behavior is meaningful and helpful.

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

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

The description is two concise sentences with no redundancy. The primary purpose is front-loaded, and the special behavior for running tasks is added as a separate clarifying clause. Every word 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 tool with three parameters and no output schema, the description covers the core purpose and behavioral nuance. It does not explain the mode parameter's effect or expected return, but these are either covered by the schema or not essential for invoking the tool correctly. The description is adequate, though it could mention more about post-resume outcomes.

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

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

Schema description coverage is 100%, so all parameters (task_id, message, mode) are already documented in the schema. The description adds no additional parameter context beyond what the schema provides, so 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 states a specific verb ('send instruction'), resource ('task'), and target states (completed or stopped), and explicitly notes the behavior for running tasks (stop then resume). This clearly distinguishes it from siblings like dispatch_task (creating new tasks) and stop_task (only stopping).

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

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

The description implies when to use the tool—for resuming sessions of completed/stopped tasks—and explains the special case for running tasks. It does not explicitly name alternatives or exclusions, but the context of sibling tools and the described behavior makes the usage scenario clear.

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

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

No annotations are provided, so the description carries the full burden. It does disclose the cleanup=true side effect of removing the task from the registry and CLI, but it does not explain reversibility, error behavior, or consequences for tasks that are not running.

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

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

The description is extremely compact, front-loads the core action, and then adds the conditional cleanup detail. Every word contributes 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?

For a simple 2-parameter tool, the description covers the core action and the cleanup option, but with no output schema and no annotations it omits return/error behavior and edge cases such as stopping a task that is not running. The description 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%, which gives a baseline of 3. The description adds concrete meaning beyond the schema by specifying that cleanup=true removes the task from the registry and CLI, which is more informative than the schema's generic '是否同时清理' phrasing.

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

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

The description states a specific verb ('stop') and a specific resource ('running task'), and it adds the cleanup behavior. This clearly distinguishes it from sibling tools like dispatch_task, get_task_status, and list_tasks.

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 this tool is for stopping a running task, but it does not explicitly say when to use it versus alternatives, nor does it mention exclusions such as already-stopped or completed tasks. No alternative routing is provided.

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