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 discloses nothing: not whether it is a read-only call, what authentication/session profile is required, what 'base data' actually contains, or how it relates to the host/port/scheme/profile connection parameters.

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?

It is a single short sentence with no wasted words and nothing to trim, but its brevity reflects under-specification rather than disciplined conciseness. Structure is fine; content is thin.

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 four optional connection parameters, no annotations, and an output schema that only spares the description from explaining return values, the description still leaves the agent unable to tell what this tool does that its many app_* siblings do not.

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 host, port, scheme, and profile in Chinese. The description adds no additional meaning about these parameters, so the baseline 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?

The description ('获取应用中心基础数据' / 'Get app center basic data') is essentially the title restated in Chinese, with no specific verb+resource beyond 'get' and the vague noun 'basic data'. It does not distinguish this tool from siblings like app_list, app_status, or app_config_sys, which all plausibly return 'app center' information.

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

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

There is no guidance on when to use this tool versus the many other app_* siblings (app_list, app_status, app_entry_list, app_desktop_list, etc.). No prerequisites, no exclusions, no alternatives are named.

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 disclosure burden, and it only restates the purpose. It does not clarify that this is a read-only query (vs. app_update which mutates), whether authentication is required, whether it can be run at any time, or any other operational behavior.

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

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

A single, short, front-loaded sentence with no wasted words. It is appropriately minimal, though the terseness leaves little room for the guidance that is missing elsewhere.

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?

An output schema exists, so return values need not be described, and all parameters are documented in the schema. What remains missing is usage/behavioral context, and without annotations the description should say more about when and why to run this check.

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 all four parameters (host, port, scheme, profile), so the schema already documents each one. The description adds no parameter semantics beyond that, so the baseline 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?

The description states a specific verb+resource (check for updates of installed applications), which an agent can distinguish from siblings like app_update (actual update) and app_store_latest_release. However, it does not explicitly name or contrast those siblings, so 4 rather than 5.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as app_update, app_config_auto_update, or app_store_latest_release. The usage is only implied by the word 'check'.

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 usefully discloses the read/write duality and the exact trigger for the mutation path, but says nothing about permissions required, what happens to running apps when the volume changes, reversibility, 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?

A single sentence that front-loads the read/write scope and wastes nothing. Optimal size for a five-parameter tool whose parameters are self-documented.

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?

An output schema exists, so return values need not be explained. However, for a tool that can mutate configuration on a NAS with zero annotations, the description omits any note on permissions, risk, or effect on dependent apps, leaving the mutation path under-described.

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 host/port/scheme/profile are already documented in the schema. The description only adds semantic weight for set_volume (non-empty implies write), which is the baseline-3 level of added 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 names a specific verb pair (查询/设置, i.e. query/set) and a specific resource (应用公共卷, the app common volume), so an agent can tell what the tool does. It does not, however, differentiate itself from nearby app/config or file_app_dir_list siblings, leaving some ambiguity about which volume concept this covers.

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 parenthetical states the condition that switches the tool into write mode (set_volume 非空), which is implicit usage guidance for a dual-mode tool. There is no explicit when-to-use versus alternatives, no prerequisites (e.g. login/profile), and no 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, yet the single sentence discloses nothing beyond the purpose. It does not confirm the operation is read-only, state any auth/permission requirement, or note whether host/port/profile affect which NAS instance is queried.

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?

A single front-loaded sentence with no redundant or filler text. It is terse to the point of under-specification, but for the conciseness dimension it is clean and appropriately sized.

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?

An output schema exists, so return values need not be described, and the schema fully documents the five parameters. What is missing is the connective context an agent needs to route correctly: how this differs from the app_openapi auth-path siblings and any session/connection prerequisites.

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%, including a helpful note that app_name comes from app_list's appName field rather than the display name, so the schema does the heavy lifting. The description adds no parameter meaning of its own; baseline 3 applies.

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

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

The description states a specific verb (查看/view) and resource (应用的鉴权路径配置/app's auth path configuration), so an agent knows this reads auth path config for a given app. It does not, however, distinguish itself from nearby siblings such as app_openapi_allow_auth_paths or app_openapi_add_auth_path, which also deal with auth paths.

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

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

There is no when-to-use guidance, no prerequisites (e.g., must the app be installed or login performed first), and no mention of any alternative tool. The agent must infer usage entirely from the tool name.

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

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

No annotations are provided, so the description carries the full behavioral burden. It notes that this is a write operation, which is helpful, but does not explain required permissions, reversibility, or what effect the toggle has on the application. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single efficient sentence with the core purpose front-loaded. It is concise and wastes no words. However, for a tool with six parameters and no annotations, it is arguably too terse to be fully structured for the agent.

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?

An output schema exists, so return values need not be explained. The schema covers most parameters. Yet the description omits usage context, sibling differentiation, and richer behavioral details for a mutation tool, leaving clear gaps despite the structured data available.

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 high (83%), so the input schema already documents most parameters well, including app_name source and connection details. The description adds no additional parameter meaning beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description states a clear verb+resource: toggling app auto-update on/off. It is specific and distinguishes itself from general app update operations like app_update or app_check_update. However, it does not explicitly differentiate itself from sibling config tools such as app_config_set.

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 no guidance on when to use this tool versus alternatives like app_config_set or app_update. It only implies usage from the toggle action. There are no prerequisites, conditions, or exclusions 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 the full behavioral burden. '查看' implies a read-only operation, which is some signal, but there is no disclosure of auth/permission requirements, whether it targets a running app, or any rate/side-effect behavior.

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

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

A single, front-loaded sentence with no filler. It is efficient, though its brevity borders on under-specification for a five-parameter tool.

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?

An output schema exists, so return values need not be explained. However, for a five-parameter tool with zero annotations, the description does not compensate for the missing safety/permission context, leaving it only minimally 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?

Schema description coverage is 100%, so all five parameters (including the nuanced app_name-vs-name distinction) are already documented in the schema. The description adds no additional parameter meaning, so the baseline 3 applies.

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

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

States a specific verb+resource ('查看...配置项详情' – view config item details) scoped to '指定应用' (a specified app). This distinguishes it reasonably from the list/config-family siblings, though it never explicitly contrasts with app_config_list or app_config_sys.

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 indication of when to use this versus app_config_list, app_config_sys, or app_config_auth_paths, and no prerequisites (e.g., that the app must be installed or that app_name comes from app_list). Usage must be entirely inferred.

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 only says it lists app config items and gives no information about read-only safety, authentication requirements, or side effects. The output schema covers return values, but behavioral traits remain undisclosed.

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

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

One short sentence with no filler and the purpose front-loaded. It is appropriately concise, though brevity comes at the cost of not addressing sibling differentiation.

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 output schema exists, so return values need not be explained, and all parameters have schema descriptions. However, in a large sibling set including app_config_detail, app_config_sys, and app_config_set, the description does not fully clarify when this list tool should be chosen over those alternatives.

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 four parameters (host, port, scheme, profile) are already well documented in the schema. The description adds no additional parameter meaning, which is the expected baseline when schema coverage is high.

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

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

States a specific verb (列出) and resource (应用的配置项) with scope (所有应用). Clear at a basic level, but does not explicitly distinguish itself from siblings such as app_config_detail, app_config_sys, or app_config_set.

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 app_config_detail or app_config_sys, and no prerequisites or context are provided. The agent must infer usage entirely from the name.

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

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

No annotations are provided, so the description carries the full burden. It discloses that this is a write operation, but says nothing about required permissions, reversibility of the toggle, what existing proxy state is overwritten, or side effects. For an unannotated mutation tool this is a significant gap.

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

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

A single front-loaded sentence with no filler; the scope (app external proxy) leads and the write tag trails. It is efficient, though extremely terse given the tool's 6 parameters.

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?

An output schema exists, so return values need not be explained. However, for an unannotated write tool with 6 parameters the description is thin on side effects and prerequisites, leaving it only minimally 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?

Schema coverage is 83%, so the schema already documents most parameters (host, port, scheme, profile, app_name). The description adds nothing about the allow flag or app_name semantics, so the baseline 3 applies.

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

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

The description states a specific verb+resource: allowing/denying an app's external-network proxy access, and flags the write nature. It is distinguishable from the many app_config_* siblings (list, detail, set, wizard) which deal with general config, though it does not explicitly name an alternative.

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

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

There is no guidance on when to choose this over app_config_set, app_config_set_sys, or app_config_auth_paths, nor any prerequisites. The only implicit signal is the '(写操作)' tag, which marks it as a mutation but does not route the agent among 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?

No annotations are provided, so the description carries the full behavioral burden. It discloses that fields is a JSON object '透传' (passed through), which is useful, but says nothing about whether writes merge with or replace existing config, what permissions are required, or reversibility.

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

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

Two short, front-loaded sentences with zero filler; the write-operation qualifier comes immediately. The terseness is efficient, though it borders on under-specification for a mutation tool.

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?

An output schema exists, so return values need not be explained, but for a six-parameter write tool with no annotations the description is too sparse. Merge-vs-replace semantics of the fields object and any auth requirements are absent, leaving the agent without key operational context.

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 six parameters including app_name's source (app_list) and host/port/scheme details. The description's note that fields is a pass-through JSON object adds minor value, but does not exceed the schema baseline.

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

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

The description states a specific verb (修改/modify) and resource (应用配置项/app config), plus flags it as a write operation, so an agent immediately knows what it does. However, it offers no differentiation from the very close sibling app_config_set_sys, which is also a config-write tool, leaving the agent to guess which one applies.

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

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

There is no when-to-use guidance, no mention of alternatives, and no prerequisites or exclusions. The only implicit cue is the parenthetical '写操作' (write operation), which does not tell the agent when to choose this over app_config_set_sys or app_config_list.

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 does disclose two meaningful behavioral traits: it is a write operation and it affects global application behavior. However, it omits permissions required, reversibility, merge/replace semantics for the 'fields' object, and any rate or auth constraints.

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 single sentence is front-loaded with the verb and resource and contains no filler. It is appropriately concise, though its brevity leaves it under-informative for the tool's complexity.

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

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

For a six-parameter, nested-object write tool that changes global app behavior, the description does not explain field expectations, required privileges, or alternative siblings. An output schema exists, so return values need not be covered, but the missing usage and behavioral detail leaves significant gaps.

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

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

Schema description coverage is 83%, so the schema already documents host, port, fields, scheme, and profile. The description mentions no parameters and adds no meaning beyond the schema, which fits the baseline 3 when structured data carries the load.

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

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

The description names the specific action ('修改') and resource ('应用中心系统配置'), and clarifies it is a write operation affecting global app behavior. It does not explicitly differentiate itself from the sibling app_config_set or other app_config_* tools, so an agent gets a clear purpose but no sibling routing.

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

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

There is no guidance on when to use this tool versus app_config_set, app_config_auto_update, or other config tools, nor any prerequisites or exclusions. The only usage signal is the generic parenthetical that it is a write operation with global impact.

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 supplied, so the description carries the full burden. The verb 查看 implies a read-only call, but nothing is said about authentication/session requirements (the profile param hints at session scoping), whether the returned config includes secrets, or what happens when host/port are omitted and defaults are resolved.

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?

A single short sentence that is front-loaded and free of filler. It is efficiently written, though the brevity stems partly from under-specification rather than deliberate density.

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?

An output schema exists, so return-value explanation is not required, and all four optional connection parameters are documented. Still, the description leaves unclear what specific configuration is retrieved and how it differs from the sibling config-read tools, which matters given the crowded app_config_* namespace.

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

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

Schema description coverage is 100%, with host, port, scheme, and profile all documented in the schema itself (including example ports and protocol options). The description adds nothing beyond this, so the baseline of 3 for fully documented schemas applies.

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

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

The description gives a verb (查看) and a resource (应用中心系统配置), so the basic operation is identifiable. However, it does not distinguish this from closely named siblings such as app_config_list, app_config_detail, or app_config_set_sys, leaving the reader unsure what 'system config' covers versus generic app config.

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

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

There is no guidance on when to use this tool versus app_config_list, app_config_detail, or the other app_config_* siblings. No prerequisites, no exclusions, and no mention of how it relates to the mutation counterpart app_config_set_sys are provided.

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 reveals only that the output is a wizard/form definition; it says nothing about whether this is a read-only fetch, whether authentication or a live session profile is required, or any side effects — significant gaps for a tool with connection-oriented parameters (host/port/scheme/profile).

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?

A single short sentence with the resource and clarifying parenthetical front-loaded; nothing is padded or wasted. It is efficient, though arguably under-specified rather than optimally sized.

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?

An output schema exists, so return-value explanation is not required, and the schema fully covers parameters. However, with no annotations and no usage guidance, the description does not fully support correct invocation of a five-parameter, connection-aware tool.

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

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

Schema description coverage is 100%, so the schema already documents all five parameters including the app_name lookup convention. The description adds no additional parameter meaning, which is acceptable at this coverage level, giving the baseline 3.

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

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

The description names a specific verb+resource ('获取应用配置向导数据') and clarifies the payload as an installation wizard form definition. This is more specific than a bare restatement, but it does not distinguish itself from siblings like app_config_detail or app_config_list that also retrieve app configuration.

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

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

There is no statement of when to use this tool versus the many app_config_* siblings, no prerequisites, and no conditions for invocation. The agent is left to infer usage entirely from the name and the app_name requirement.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, yet it only says the tool lists icons. It does not mention authentication/connection requirements implied by the host/port/scheme/profile parameters, nor scoping (e.g., per-user desktop), nor anything about the result set.

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?

A single short, front-loaded sentence with no wasted words. It is efficient, though the brevity borders on under-specification rather than true conciseness.

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?

An output schema exists, so return values need not be explained, and the schema itself covers the connection parameters. Still, for a tool with four connection-oriented parameters and no annotations, the description is thin on how it fits alongside sibling list 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%, with all four connection parameters (host, port, scheme, profile) fully documented in the schema. The description adds nothing beyond the schema, so the baseline 3 applies.

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

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

The description states a specific verb+resource ('列出桌面应用图标' – list desktop app icons), so the basic action is understandable. However, it gives no differentiation from closely-related siblings such as app_list and app_entry_list, leaving the agent to guess which listing is appropriate.

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

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

There is no guidance on when to use this tool versus app_list, app_entry_list, or app_list-style siblings, and no exclusions or prerequisites are stated. The agent must infer usage entirely from the name.

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

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

No annotations are provided, so the description carries the full disclosure burden. It does flag that this is a write operation ('写操作'), which is genuinely useful, but it says nothing about whether cancellation is reversible, what happens if the task is already complete or missing, whether it needs elevated permissions, or what side effects occur on the NAS. For a destructive mutation with zero annotation coverage this is thin.

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

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

A single short sentence with the operation front-loaded and no wasted words. It is efficient, though the extreme brevity is part of why guidance is missing.

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?

An output schema exists, so return values need not be explained, and the parameter surface is fully documented in the schema. What is missing is the disambiguation from sibling cancel tools and any behavioral caveats for a write operation, leaving the definition minimally viable rather than complete.

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

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

Schema description coverage is 100%, so every parameter (including host/port/scheme/profile connection details and task_id) is already documented in the schema. The description adds no format, sourcing, or constraint information about task_id beyond what the schema states, so the 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 gives a specific verb+resource pair ('取消应用商店下载任务' – cancel an app-store download task), so the agent knows exactly what operation this performs. It does not, however, distinguish itself from the numerous other cancel tools in the sibling list (app_task_cancel, app_install_cancel, app_update_cancel, download_action), which is the main purpose-clarity gap.

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

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

There is no statement of when to use this tool versus the closely related cancel siblings (app_task_cancel, app_install_cancel, app_update_cancel) or any prerequisite such as needing a valid task_id from a prior download task. Usage can only be inferred from the name and the fact that it is a write operation.

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 at all, the description carries the full disclosure burden. It never states that this is a read-only listing, what host/port/profile context it needs, or whether it hits a network session — it only explains the only_hidden toggle. For a connection-parameterized tool, this is a significant behavioral gap.

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

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

Two tight clauses, front-loaded with the purpose and immediately followed by the flag semantics; nothing is wasted. It is arguably under-written for a five-parameter tool, but as pure concision it succeeds.

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?

An output schema exists, so return values need not be described, and schema text covers most connection parameters. However, the description says nothing about what an 'entry' is, how it relates to sibling listing tools, or the read-only nature, which leaves real gaps for a tool in a crowded family.

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 80%, and the description precisely fills the single undocumented parameter by explaining that only_hidden=True restricts results to hidden entries — semantics not present in the schema for that field. It adds no extra meaning for host/port/scheme/profile, but those are already documented.

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 verb+resource (list app entries) but '入口' is ambiguous — it could mean launcher/desktop shortcuts or app registration entries, and siblings like app_desktop_list, app_service_list, and app_list make that distinction critical. Nothing in the description tells the agent how this differs from those siblings, leaving the tool only loosely identifiable.

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 only guidance is the behavior of the only_hidden flag; there is no statement of when to call this tool, no prerequisites, and no named alternative despite several closely-named sibling listing tools. The agent must guess its place among the app_* family.

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 discloses only that this is a write operation ("写操作"); it says nothing about permissions required, partial-failure behavior for a batch install, prerequisites for the guide flow, or reversibility — significant gaps for a batch mutation.

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?

A single short clause with zero waste and the key fact (batch write) front-loaded. It is appropriately sized, though its brevity reflects under-specification rather than true economy.

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?

An output schema exists, so return values need not be explained. But for a 6-parameter batch write with no annotations, the description omits the guide-flow prerequisites and the relationship to the optional connection parameters, leaving the definition only minimally 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?

Schema description coverage is 100%, so the schema already documents all six parameters (host, port, scheme, profile, app_names, volume_id). The description adds no parameter meaning beyond that, so the baseline 3 applies.

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

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

States a specific verb+resource — "批量安装商店应用" (batch install store apps) — plus the context of the installation guide flow. However, it does not differentiate itself from nearby siblings like app_install or app_install_fpk, so an agent cannot tell from the description alone why the batch/guide variant is the right pick.

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 phrase "装机引导流程" implies the guide-flow context, but there is no explicit when-to-use guidance, no when-not-to-use, and no named alternative such as app_install. The agent must infer the routing decision entirely.

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 of behavioral disclosure. "检查" (check) implies a read-only operation and "批量" indicates batching, but there is no mention of authentication needs, network requirements, idempotency, error behavior, or whether the host/port/profile parameters affect behavior. The output schema exists but the description adds no behavioral context.

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

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

The description is a single compact sentence with no filler and the purpose is front-loaded. It is appropriately sized for a simple check tool, though it could be slightly more structured by naming the sibling alternative.

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 conceptually simple, has an output schema, and 100% schema description coverage, so the description does not need to explain returns or parameters. However, it omits usage context relative to siblings and provides minimal behavioral detail, leaving the agent with enough to invoke the tool but not enough to choose it confidently over related 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 all five parameters. The description does not add any parameter syntax, format, or usage details beyond what the schema provides, so the 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?

The description states a specific verb and resource: "批量检查应用是否已安装" (batch check whether apps are installed). It also adds the context "（装机引导）" (installation guide). However, it does not distinguish the tool from siblings like app_status or app_guide_batch_install, 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 parenthetical "（装机引导）" implies the tool is meant to be used in the installation-guide flow, but there is no explicit when-to-use, when-not-to-use, or alternative tool guidance. Usage is only weakly implied rather than 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?

With no annotations, the description carries the full behavioral burden. It usefully discloses that this is a write operation and that dry_run=True produces a preview only — meaningful traits beyond the schema. But it omits permission/auth requirements, side effects of a real install, and interaction with async task tools (app_task_status), leaving substantial gaps for a mutation 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 short, front-loaded sentences with no filler: the write nature leads, then the dry_run caveat. It is efficient, though arguably under-sized for a 12-parameter operation.

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 12-parameter install mutation with no annotations, the description is thin. An output schema exists so return values need not be explained, but the description lacks guidance on required args, host/profile selection, and how the install relates to sibling task/status tools — gaps that matter more given the tool's complexity.

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

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

Schema description coverage is high (75%), so the schema documents most parameters, warranting a baseline of 3. The description does add value by explaining dry_run, which has no schema description, but the many other undocumented-or-shallow params (no_start, accept_license defaults, volume targeting) get no additional meaning from the prose.

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

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

States a specific verb+resource (安装应用 = install an app), which is clear on its own. However it does not differentiate from closely-related siblings such as app_install_fpk (install from an fpk file) or app_guide_batch_install, so an agent cannot route confidently among the install-family tools from the text 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 only conditional guidance is about dry_run behavior, which is parameter semantics rather than when-to-use guidance. There is no statement of when this tool should be chosen over app_install_fpk, app_guide_batch_install, or app_store_detail/app_update, nor any exclusions or prerequisites (auth, required host/profile).

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 one important trait — that this is a write operation (写操作) — but says nothing about reversibility, required permissions, whether the task_id must reference an active install, or what happens on an invalid/expired task id.

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?

A single front-loaded sentence with zero filler; the operation and its mutating nature are stated immediately.

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?

An output schema exists, so return values need no explanation, and the 5 parameters are fully described in the schema. However, for a mutation tool with no annotations, the description is thin on safety/permission context and gives no routing guidance among the several cancel siblings.

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

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

Schema description coverage is 100%, so every parameter including the required task_id is already documented in the schema. The description adds no additional parameter meaning (formats, defaults, constraints), so the baseline 3 applies.

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

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

States a specific verb (取消/cancel) and resource (应用安装任务/app install task), so the agent knows exactly what operation is performed. It does not differentiate itself from closely named siblings like app_task_cancel, app_update_cancel, or app_download_cancel, so it falls 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 no when-to-use guidance, no prerequisites (e.g. an in-progress install task must exist), and no indication of when to prefer app_task_cancel, app_update_cancel, or app_download_cancel instead. The agent must infer the correct tool purely from the name.

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

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

With no annotations, the description carries the full behavioral burden and only discloses one trait: that this is a write operation (写操作). It says nothing about required permissions/scope, that accept_license defaults to true (automatic license acceptance), cancellation behavior (cancel_on_failure, app_install_cancel), or side effects on an existing app version. For a 14-parameter mutation tool the disclosure is thin.

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

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

A single sentence that front-loads the action and immediately follows with the two most decision-relevant facts (write operation, source either/or). No filler, nothing restated from the title.

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 14-parameter write tool with zero annotations, the description is far too sparse; the output schema covers return values, but an agent still lacks permissions, license-behavior, and failure/cancel context. It covers the minimum to identify the tool and not much more.

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 71%, so the schema already documents most parameters and the baseline is 3. The description adds only the mutual-exclusivity of remote_path and local_file, which the schema arguably also implies; it adds nothing about host/port/scheme, volume_id vs data_volume_id, or the unlabeled dry_run/no_start toggles.

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

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

States a specific verb (安装/install) and resource (应用/app) and qualifies the source as an 'fpk 离线安装包', which meaningfully distinguishes it from the online/store install siblings like app_install and app_store_detail. It stops short of naming those siblings explicitly, so an agent still infers the boundary rather than being told 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 parenthetical '写操作；remote_path 或 local_file 二选一' gives an operational constraint (choose one of two source paths) and flags the write nature, which is genuine usage guidance. However, there is no statement of when to prefer this tool over app_install, app_guide_batch_install, or the store install path, nor any prerequisite/exclusion guidance.

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

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

With no annotations, the description carries the full burden, and it does disclose one high-value behavioral trait: the appName vs name distinction and the exact failure ("installed app not found") for getting it wrong. However, it says nothing about authentication/session requirements, connection behavior for host/port/scheme/profile, or rate limits, leaving sizable behavioral gaps for a tool with zero annotation coverage.

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 short sentences, purpose front-loaded, then the one operational detail that actually matters. No filler, and the warning about the wrong identifier is placed where an agent will read it before calling downstream app_* tools.

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 task is a simple read and an output schema exists, so return shapes need not be re-explained; the description's mention of appName/name earns its place by adding the downstream-selection semantics. Connection/authentication context is thin, but for a simple listing tool the definition is close to complete.

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

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

Schema description coverage is 100% with all four parameters (host, port, scheme, profile) documented in the schema, so the baseline is 3. The description adds no information about these parameters — it only discusses output fields — so it does not exceed the baseline.

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

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

The description opens with a specific verb+resource ("列出已安装的应用" — list installed apps), which cleanly separates it from siblings like app_store_list or app_status. It never names a sibling it should be preferred over, so it stops short of full differentiation, but an agent can identify the operation immediately.

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?

It implicitly defines this tool's role as the discovery step feeding every other app_* tool, and states the precondition (must use appName from this output) concretely. There is no explicit when-not-to-use or alternative-tool guidance, so it is clear context rather than complete routing.

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 disclosure burden and falls short. It says only that this is a write operation; it does not state what the inherit file affects, whether it overwrites existing config, required permissions/session profile behavior, or whether the change is reversible.

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?

A single short sentence with zero padding and the resource front-loaded. It is appropriately sized for what it says, though the brevity reflects missing content rather than disciplined editing.

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?

An output schema exists, so return values need not be described. But for a 6-parameter mutation tool with no annotations and three confusingly similar siblings, one sentence is not enough — it omits the effect of the write, prerequisites, and sibling disambiguation.

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

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

Schema description coverage is 100%, with each of the six parameters (host, path, port, scheme, profile, app_name) documented in-schema, so the baseline is 3. The description adds nothing beyond the schema — notably it does not clarify the difference between 'path' (鉴权继承文件路径) used here versus the auth-path concepts in the sibling tool.

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?

Names a specific verb (添加/add) and resource (OpenAPI 鉴权继承文件/auth inherit file), and flags it as a write operation, so the action is unambiguous. However it gives no signal distinguishing itself from the near-identical sibling app_openapi_add_auth_path (or app_openapi_allow_auth_paths), leaving the agent to guess which of the two write tools applies.

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

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

There is no when-to-use guidance, no prerequisite (e.g. app must already exist / appName from app_list), and no mention of the alternatives app_openapi_add_auth_path or app_openapi_allow_auth_paths. The only usage cue is the parenthetical '(写操作)', which restates the obvious instead of routing the agent.

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

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

No annotations are provided, so the description carries full behavioral burden. It only signals '(写操作)' (write operation); it omits permission/admin requirements, whether the path is appended or replaces existing entries, idempotency, and any side effects on running services.

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?

A single short clause with no filler and the write-operation qualifier front-loaded in parentheses. It is efficient, though arguably too terse to be fully 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?

An output schema exists, so return values need not be described, and all six parameters are documented in the schema. The remaining gap is contextual: no indication of required context (app installation state, OpenAPI enablement) or relation to sibling auth-path tools for a 6-parameter mutation.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds nothing beyond the schema about app_name, path, host, port, scheme, or profile semantics, meaning the schema does all the explanatory work.

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

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

States a specific verb and resource: adding an OpenAPI auth path for an application, plus the parenthetical '(写操作)' flags it as a mutation. It does not, however, distinguish itself from close siblings such as app_openapi_allow_auth_paths or app_openapi_add_auth_inherit_file.

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 when-to-use guidance, no prerequisites (e.g. that the app must be installed or the OpenAPI service enabled), and no mention of how this differs from app_openapi_allow_auth_paths or app_openapi_add_auth_inherit_file. The agent must infer placement among neighboring auth-path 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, the description carries the full behavioral burden, and it only implies read-only via '查询'. It says nothing about permission/auth requirements, whether app_name must reference an installed app, or the scope of the returned path list.

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?

A single front-loaded sentence with zero filler. It is efficient, though arguably under-specified rather than optimally concise.

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?

An output schema exists, so return values need not be explained, and the schema fully documents parameters. However, with no annotations the description should carry more behavioral context (auth needs, scope, relationship to sibling add/query tools) than the one-line query statement provides.

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 five parameters (including the app_name provenance note). The description adds no parameter meaning beyond that, which is the baseline 3 when the schema does the heavy lifting.

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

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

The description states a specific verb (查询/query) and resource (应用 OpenAPI 允许的鉴权路径), so an agent can tell it is a read operation over OpenAPI auth paths. It does not explicitly distinguish itself from close siblings like app_openapi_app_detail or app_config_auth_paths, keeping it 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?

There is no guidance on when to use this tool versus the sibling auth-path tools (app_config_auth_paths, app_openapi_add_auth_path), nor any stated prerequisites such as needing an app installed. Usage is only implied by the verb '查询'.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The verb '查询' implies a read operation, but nothing is said about authorization requirements, rate limits, or what happens on failure. This is a significant gap for a tool with zero annotation coverage.

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 with no wasted words and is front-loaded. However, it merely restates the tool title and name, providing no additional 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?

An output schema exists and schema coverage is full, so return values and parameters need little explanation. But the description omits any usage context and fails to differentiate this tool from the numerous app_openapi_* siblings, leaving an agent without enough information to select it confidently.

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 every parameter in detail, including the app_name sourcing note. The description adds no parameter information beyond that, so the 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 '查询应用 OpenAPI 详情' states a verb (query) and a resource (application OpenAPI details), but 'OpenAPI 详情' is vague about what is actually retrieved. It does not distinguish this tool from siblings like app_openapi_allow_auth_paths or app_openapi_add_auth_path, which also concern app OpenAPI configuration.

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

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

The description offers no when-to-use guidance, no prerequisites, and no alternatives. An agent cannot tell from this text when to choose app_openapi_app_detail over the other app_openapi_* 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, the description carries the full behavioral burden, yet it only states that settings are viewed. It does not disclose auth/session requirements, whether the host/port/scheme parameters establish a connection, or whether any state is affected. The read-only nature is only implied by '查看'.

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?

A single short, front-loaded sentence with zero padding. It is efficient, though its brevity tips into under-specification for a tool with four parameters and a broad resource name.

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?

An output schema exists so return values need not be described, and all parameters are schema-documented. But for a settings-inspection tool surrounded by many similar app_config_* siblings, the description provides no scope, no connection expectations, and no routing guidance, leaving the agent unable to choose or invoke it confidently.

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%: host, port, scheme and profile all have Chinese descriptions in the schema, so the schema does the explanatory work. The description adds no additional meaning about these parameters, which matches the baseline 3 for high-coverage schemas.

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 gives a verb-plus-resource ('查看应用运营设置' = view app operation settings), which is better than a tautology, but '运营设置' is vague and the description offers no differentiation from the many sibling app_config_* tools (app_config_list, app_config_sys, app_config_detail). An agent cannot tell from this text alone which settings this returns.

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

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

There is no when-to-use guidance, no mention of alternatives such as app_config_sys or app_config_list, and no conditions or prerequisites. The agent is left to infer that this is the tool for a specific subset of app settings.

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 behavioral burden. The parenthetical '(写操作)' usefully flags this as a mutating operation, but nothing is said about service interruption, required permissions, whether the app must be stopped first, or what state results — all critical for a disruptive lifecycle 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?

A single front-loaded phrase with zero filler, which is efficient. It is arguably too terse for a mutating tool, but there is 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?

The presence of an output schema excuses explaining return values, but for a 5-parameter mutating tool with no annotations the description is far too thin — it omits targeting guidance, prerequisites, and the impact of a restart.

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 host, port, scheme, profile and app_name in detail (including the appName-vs-name caveat). The description adds nothing beyond that, so the baseline 3 applies.

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

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

States a specific verb and resource ('重启应用' / restart application), which is unambiguous on its own. However, it does not distinguish this from the many sibling lifecycle tools (app_start, app_stop, app_install), so an agent gets no help choosing among them.

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

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

There is no when-to-use guidance, no prerequisites (e.g. app must be running), and no mention of the alternative siblings app_start/app_stop. The agent must infer the restart scenario entirely.

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, and it discloses almost nothing: no statement that this is a read-only listing, no auth/profile requirements, no note on whether host/port/scheme must resolve to a reachable NAS, and no indication of result scope or pagination.

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?

A single short sentence with the resource front-loaded and zero filler. It is efficient, though the extreme brevity is arguably under-specification rather than true conciseness.

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?

An output schema exists, so return values need not be explained, and all four params are optional with documented defaults. What is missing is any hint of context an agent needs to pick this tool — what 'SAC' means and how it relates to the other app-store listing siblings.

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

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

Schema description coverage is 100%, so all four parameters (host, port, scheme, profile) are already documented in the schema with defaults and examples. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the work.

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

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

States a verb (获取) and resource (SAC 应用商店列表), and the parenthetical hints at the data's nature (应用推荐数据源). However, 'SAC' is never defined, and the description gives no way to distinguish this from the sibling app_store_list or app_store_latest_release — the agent cannot tell why one list endpoint would be chosen over the other.

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

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

There is no when-to-use, when-not-to-use, or alternative-tool guidance at all. With app_store_list, app_store_search, and app_store_latest_release as siblings, the absence of any routing signal is a real gap.

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. '列出' implies a read-only operation, but the description says nothing about authentication requirements, whether a session/profile is needed, rate limits, or any other behavioral trait. This is a significant gap for a tool with no 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?

The description is a single short sentence, front-loaded with the action and object, with no wasted words. It is appropriately sized for the minimal information it conveys.

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 has an output schema (so return values need not be described) and complete parameter documentation, the remaining gap is behavioral and usage context. The description does not say which application's services are listed, how they are selected, or how this differs from numerous sibling app_* listing tools. It is barely complete for an agent to invoke correctly without confusing it with siblings.

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

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

Schema description coverage is 100%, so the schema already documents host, port, scheme, and profile in detail. The description adds no parameter meaning beyond what is already in the schema. 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 states a specific verb and resource: '列出' (list) '应用提供的服务' (services provided by the application). It is clear enough to distinguish a listing operation, but it does not differentiate from siblings like app_list, app_entry_list, or app_desktop_list.

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

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

There is no guidance on when to use this tool instead of alternatives such as app_list or app_entry_list, nor any prerequisite or exclusion conditions. The agent must infer its role entirely from the name and sibling list.

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 disclosure burden. It does note that this is a write operation, but says nothing about permissions, whether the app must be installed/stopped first, whether the call is asynchronous (relevant given siblings like app_task_status), or how failures surface.

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?

A single front-loaded sentence with a useful parenthetical tag and zero filler. It is tight and well-structured, though the extreme brevity leaves no room for the routing or prerequisite information an agent needs.

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 schema is fully described and an output schema exists, so return values need not be explained. However, as a mutation tool with no annotations, it omits essential context: prerequisites, async/task behavior, and relationship to app_stop/app_restart. The description is far too thin for the tool's complexity.

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

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

Schema description coverage is 100% and each of the five parameters (host, port, scheme, profile, app_name) is documented in the schema, including the app_name hint to use app_list's appName field. The description adds no parameter information, so the baseline 3 applies.

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

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

The description gives a clear verb+resource pair ('启动应用' = start app) plus a mutation marker ('写操作'), so an agent immediately knows this starts a specific application. It is naturally distinguishable from app_stop/app_restart by verb semantics, but it never names or contrasts those siblings, so it stops short of a 5.

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

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

There is no when-to-use guidance, no prerequisites (must the app be installed? stopped?), and no mention of the alternatives app_restart or app_install. The only contextual hint is the parenthetical '(写操作)', which flags a mutation but does not route the agent between 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?

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing beyond the title. It does not state that this is a read-only, non-mutating query, nor what kind of status (running/stopped/installing) it returns. It adds essentially no behavior context over the name and schema.

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

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

A single front-loaded sentence with zero filler. It is appropriately terse for a simple read tool, though arguably so brief that it omits useful context.

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?

An output schema exists, so return values need not be explained, and the schema fully documents parameters. For a single-resource read tool this is minimally adequate, but the description still omits the behavioral basics (read-only nature, relationship to the app lifecycle siblings).

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

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

Schema description coverage is 100%, with the app_name parameter well documented (including that it comes from app_list's appName field, not the display name). The description adds no parameter detail beyond the schema, so the baseline 3 applies.

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

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

States a clear verb and resource: query the status of a single app (查询单个应用状态). The word 单个 (single) implicitly contrasts with the many list-style siblings like app_list. However, it does not name any sibling tool to differentiate explicitly, keeping it just 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?

No indication of when to use this versus alternatives such as system_info, status_overview, or the app lifecycle tools (app_start/app_stop). There are no prerequisites or exclusions stated. The agent must infer usage entirely.

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 behavioral burden, and '写操作' is the only disclosure. It does not say whether the stop is graceful or forced, what happens to dependent services or tasks, what permissions are needed, or whether the operation is reversible — all relevant for a mutation on an app.

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?

A single short sentence with zero padding and the write-operation qualifier up front. It is efficient, though the brevity reflects under-specification rather than well-chosen restraint.

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 mutation tool with no annotations and five parameters, the description omits preconditions, side effects, and failure behavior. The presence of an output schema excuses return-value detail, but not the missing operational context.

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 five parameters including how app_name relates to app_list; baseline 3 applies. The description adds no parameter-level meaning 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?

States a specific verb+resource: stopping an application, and flags that it is a write operation. However it does nothing to distinguish itself from close siblings such as app_restart and app_uninstall, which an agent must choose between by 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?

No when-to-use guidance is given. There is no indication of when to stop rather than restart or uninstall an app, no prerequisites (e.g., app must be running), and no mention of related lifecycle 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?

No annotations are provided, so the description must carry behavioral disclosure. '查看' implies a read-only operation, but the description does not state authentication requirements, rate limits, or any other behavioral traits beyond the basic 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?

The description is a single, front-loaded sentence with no wasted words. While it is under-specified for the tool's complexity, the structure itself 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?

The output schema and rich parameter descriptions reduce the description's burden for return values and parameter details. However, the description still lacks usage context and sibling differentiation, leaving it only minimally complete for an agent selecting among app-store 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 all five parameters in detail (host, port, scheme, profile, app_name). The description adds no parameter meaning beyond what the schema provides, so the baseline 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?

The description states a specific verb and resource: '查看' (view) and '应用详情' (app details) in the app store. However, it does not distinguish this tool from siblings like app_store_list, app_store_search, or app_list, so it earns a 4 rather than 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?

No guidance is given about when to use this tool versus app_store_list, app_store_search, or app_list. It also omits prerequisites such as needing an appName obtained from app_list.

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 implies a read-only fetch ('获取'), but discloses nothing about ordering, time window for 'latest', pagination, or authentication/session requirements — notable gaps given the host/port/profile session parameters.

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?

It is a single short sentence with zero filler and is front-loaded. But at this length it is under-specified rather than genuinely concise, leaving no room for the routing information an agent needs.

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 four connection parameters, no annotations, and a large sibling set of overlapping store/listing tools, the description is too thin. An output schema exists so return values need not be described, but the absence of any differentiation or session context leaves the definition incomplete for correct selection.

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% (host, port, scheme, profile all documented), so the schema already carries parameter meaning. The description adds no additional parameter context, which matches the baseline 3 for high-coverage schemas.

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

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

The description states a specific verb and resource ('获取应用商店最新上架应用'), so the general intent is clear. However, it offers no differentiation from close siblings such as app_store_list, app_store_search, and app_store_detail — an agent cannot tell from this text why it would pick 'latest release' over those.

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

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

There is no when-to-use guidance, no mention of alternatives, and no prerequisites or exclusions. The agent is left to infer the distinction between this tool and the many other app_store_* and app_* listing tools purely from the name.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, yet it says nothing about authentication requirements, pagination/result limits, whether the listing is cached, or read-only semantics. For a tool with zero annotation coverage, this is a significant gap.

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

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

A single front-loaded sentence with no filler or repetition. It is efficient, though its brevity borders on under-specification rather than genuine conciseness.

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?

An output schema exists, so return values need not be explained, and all parameters are schema-documented. Still, with no annotations and no differentiation from the many app/store siblings, the description is minimally adequate rather than complete.

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

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

Schema description coverage is 100%, so all four connection parameters (host, port, scheme, profile) are already documented in the schema. The description adds no additional parameter meaning, which is acceptable given the high coverage — baseline 3 applies.

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

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

States a specific verb (列出/list) and resource (应用商店全部应用/all apps in the app store), clearly conveying the operation. However, it does not differentiate itself from near-siblings like app_list, app_store_search, app_sac_store_list, or app_store_latest_release, so an agent still has to infer which store-view this returns.

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

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

There is no when-to-use guidance, no condition selecting it over app_store_search, app_list, or app_sac_store_list, and no exclusions. The single sentence only restates the operation and leaves routing to the agent.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it discloses nothing: no auth/profile requirement, no result count or pagination behavior, no indication of whether the search is local versus remote. 'Search' implies a read-only lookup, but this is inferred, not stated.

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?

A single, front-loaded sentence with zero filler or repetition of the title. It is efficient, though its brevity is as much under-specification as conciseness given a five-parameter tool.

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?

An output schema exists and the input schema is fully documented, so the description needn't explain return values or parameters. Still, with zero annotation coverage and no differentiation from sibling store tools, the definition is only minimally sufficient for correct selection.

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 five parameters including host, port, scheme, and profile. Baseline 3 applies because the description adds no syntax, format, or matching-semantics detail for the required keyword beyond what the schema provides.

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

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

States a specific verb and resource ('搜索应用在应用商店' = search apps in the app store), so the agent knows the action and target. However, it does nothing to distinguish itself from the many closely-named siblings such as app_store_list, app_store_detail, or app_store_latest_release, leaving the boundary implicit in the word 'search'.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. With siblings like app_store_list and app_store_latest_release present, the agent must guess which store tool applies to its situation.

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 usefully discloses that this is a write operation (写操作) and an aggregate entry, which is the most important behavioral fact for a cancel tool. It says nothing about permissions, reversibility, or whether cancelling a completed task errors out.

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

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

Two short sentences, front-loaded with the core purpose followed by the action mapping. No filler, though the wrapping/formatting of the subcommand list is slightly awkward.

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?

An output schema exists so return values need not be described, and the write-operation nature is stated. Still, the relationship to the four discrete cancel siblings is left to inference, which matters for a router-style tool with a four-value enum.

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 83%, so the schema already documents host/port/scheme/profile/task_id. The description adds value by mapping the action enum values to concrete CLI subcommands (e.g. download-cancel → app download cancel), but offers no further semantics for task_id or the connection parameters. 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?

States a specific verb and resource (cancel app tasks by type) and identifies itself as the aggregated entry point (聚合入口) whose action field maps to the individual CLI subcommands. This distinguishes it from siblings, though it does not name app_task_cancel/app_install_cancel/etc. explicitly.

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

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

The description implies the aggregate routing model by listing the CLI subcommands that action maps to, so an agent can infer usage. However, it never states when to use this tool versus the discrete sibling tools app_task_cancel, app_install_cancel, app_update_cancel, and app_download_cancel, leaving the choice implicit.

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 discloses only that this is a write operation, but does not explain irreversibility, permissions, idempotency, or what exactly gets cancelled.

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 wasted wording. However, it is arguably too terse for a 5-parameter mutation tool that has several similarly named siblings.

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?

An output schema exists, so return values need not be explained, and parameter details are covered by the schema. Still, the description does not address when to choose this tool over sibling cancels or the behavioral impact of cancellation.

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 five parameters are already documented in the input schema. The description adds no parameter-specific meaning beyond the schema baseline.

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

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

States a specific verb (取消/cancel) and resource (应用任务/app task), and tags it as a write operation. It is clear what the tool does, but it does not distinguish itself from sibling cancel tools such as app_install_cancel, app_update_cancel, or app_download_cancel.

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

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

Provides no guidance on when to use this tool versus the multiple alternative cancel tools. There is no when-to-use context, prerequisite, or exclusion 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?

With no annotations, the description carries the full burden. It never states this is a read-only query, whether it returns completion state or must be polled repeatedly, or how a finished/failed task is reported — all relevant for a progress-checking 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?

A single compact sentence that front-loads the verb and resource. No filler, though it is arguably too terse to carry the needed usage context.

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?

An output schema exists, so return values need not be explained, and the schema fully documents parameters. However the description omits the operational context (polling pattern, relationship to app_install/app_task_cancel) that an agent needs to invoke it correctly.

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

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

Schema coverage is 100%, so host/port/scheme/profile/task_id are all documented in the schema with their own descriptions. The description adds nothing beyond what the schema already provides, so the baseline 3 applies.

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

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

States a specific verb (查询/query) and resource (应用任务进度/app task progress) and scopes it to install/update/uninstall tasks. This distinguishes it from app_status (running state) and app_list, though it doesn't name a sibling explicitly.

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

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

No guidance on when to use this instead of app_status, app_task_action, or app_task_cancel. It doesn't mention that this is the polling companion to app_install/app_update, or where the task_id comes from.

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 flag the tool as a write operation ('写操作'), which is a minimal but useful signal, yet for an uninstall tool it omits the critical traits: irreversibility, whether app data/config is destroyed, permission requirements, or any confirmation/rate behavior.

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

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

A single short sentence with zero filler, and the write-operation warning is front-loaded. It is efficiently sized, though the extreme brevity borders on under-specification rather than genuine conciseness.

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?

This is a destructive mutation tool with no annotations, and the description says only that it uninstalls and is a write operation. An output schema exists, so return values need not be explained, but the absence of any warning about data loss, permissions, or irreversibility leaves the definition incomplete for its complexity.

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

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

Schema description coverage is 100%, and the schema itself documents app_name carefully (sourced from app_list's appName, not the display name) plus host/port/scheme/profile. The description adds nothing beyond the schema, so the baseline 3 applies.

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

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

States a specific verb and resource ('卸载应用' / uninstall app), so an agent knows exactly what operation is performed and can distinguish it from siblings like app_install, app_start, or app_stop. It does not, however, explicitly differentiate itself from those siblings or clarify scope (e.g., data removal).

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 no when-to-use guidance, no prerequisites, and names no alternatives. An agent is left to infer that this is the inverse of app_install purely from the name, with nothing about confirmation, dependencies, or when uninstall is appropriate versus stopping the app.

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 does disclose that this is a write operation and that dry_run only previews, which is genuinely useful. But it omits permissions/auth needs, reversibility, and what happens to a running app, leaving material behavioral gaps for an 11-param mutation 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 terse clauses, front-loading the write-operation nature and the dry-run caveat with zero 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?

An output schema exists, so return values need not be explained, and the description covers purpose plus the important dry-run behavior. It is nearly sufficient, though it could say more about side effects given the absence of annotations.

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 73%, so the schema already documents most parameters. The description adds semantics for dry_run (仅预演), which the schema leaves as a bare boolean, but contributes nothing for the remaining ten params. 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?

States a specific verb (升级/upgrade), resource (应用/app), and target (指定版本/specified version), and flags the mutation nature with 写操作. It distinguishes itself well from app_install and app_check_update by name/verb, though it doesn't explicitly call out those siblings.

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 dry_run=True clause gives a concrete preview recipe, which is real usage guidance. However, there is no explicit when/when-not versus siblings like app_install or app_check_update, so usage context is only implied.

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. The parenthetical '(写操作)' does disclose that this is a mutation, which is a small amount of genuine value, but it says nothing about permissions required, whether cancellation is reversible, what happens to a partially applied update, or any 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?

A single short sentence that is front-loaded with the action and resource, with zero filler. It is arguably too terse rather than padded, so it does not lose points for verbosity.

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?

An output schema exists, so return values need not be described. But for a write operation with no annotations, no usage routing among four similar cancel siblings, and no side-effect disclosure, the definition is materially incomplete for correct invocation.

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

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

Schema description coverage is 100%, so task_id, host, port, scheme and profile are already documented in the schema. The description adds no additional meaning about the task_id format or the connection parameters, so the 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?

States a specific verb (取消/cancel) and resource (应用更新任务/app update task), so the core action is unambiguous. However, it does not distinguish itself from the closely related sibling cancel tools (app_task_cancel, app_install_cancel, app_download_cancel), leaving the agent to guess which cancel surface applies.

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

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

There is no statement of when to use this tool, no prerequisites (e.g. an in-progress update task must exist), and no reference to the alternative cancel tools in the same family. Usage is left entirely to inference from the name.

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

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

No annotations are provided, so the description carries the full burden. It does disclose that this is a write/mutation operation and explains the src_paths-to-destination convention, which is real behavioral context. However, it says nothing about overwrite/conflict behavior (the ondup enum's effect), reversibility, or required authentication.

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?

A single compact sentence that front-loads the action and qualifies it with the operation type and the key path convention. Nothing is wasted or buried.

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

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

An output schema exists so return values need not be explained, but for a 6-parameter write tool with zero annotations the definition is thin: it omits conflict handling (ondup), host/port/scheme/profile implications, and any note on error or permission conditions.

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 83%, above the 80% threshold, so the baseline is 3. The description's only parameter-relevant statement (last src_paths item is the target directory) is already present verbatim in the schema's src_paths description, so it adds no meaning 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?

States a specific verb and resource (复制网盘文件 / copy netdisk files) and explicitly flags the operation class as 写操作. An agent can distinguish it from the sibling baidu_move without opening either schema, though no sibling is named.

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

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

Usage is implied by the parenthetical hint that the last src_paths entry is the destination directory, but there is no explicit when-to-use guidance, no comparison to baidu_move or baidu_upload, and no stated prerequisites (auth/session).

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 usefully discloses that this is a write operation and that deleted files go to the recycle bin (soft delete), which is important behavioral context. However, it omits authentication requirements, whether permanent deletion is possible, and other operational details.

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 with the core action and key behavior front-loaded. Every word earns its place and there is no unnecessary repetition.

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

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

With no annotations and a required paths parameter, the description covers the essential action and soft-delete behavior. Because an output schema exists, return values need not be explained, but the description still lacks usage context and safety-related details such as permissions needed, leaving it 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 description coverage is 100%, so the schema already documents all five parameters in detail, including paths, host, port, scheme, and profile. The description adds no parameter-level detail beyond the general concept of deleting files, so the baseline 3 applies.

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

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

The description states a specific verb (删除) and resource (网盘文件), making it clear this is the Baidu netdisk deletion tool. It does not explicitly distinguish itself from sibling tools like file_delete or baidu_move, but the resource scope is sufficiently specific for an agent to identify 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 gives no guidance on when to use this tool versus alternatives such as file_delete or baidu_move. It implies usage through its name and the parenthetical note, but provides no explicit when/when-not/alternatives information.

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 helpfully flags 写操作 (write), but omits auth/profile requirements, whether the download is asynchronous (likely, given baidu_task_list/baidu_task_info siblings), rate limits, and how the conflict default ('rename') applies.

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?

A single compact sentence with the write-operation caveat included. Efficiently front-loaded, though at the cost of omitting important usage context.

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?

An output schema exists so return values need not be explained, but for a 7-parameter download tool with zero annotations the definition says nothing about async task semantics, login/session requirements, or failure behavior — significant gaps for an agent to invoke it correctly.

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

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

Schema description coverage is 86%, so the schema already documents host, port, scheme, profile, fsids and target_path. The description adds no parameter detail beyond contextualizing the source (网盘) and destination (NAS), so the baseline 3 applies.

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

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

States a specific verb (下载/download) and both endpoints of the movement (从网盘 to NAS), plus that it is a write operation. It is clear what the tool does, though it does not name the contrasting siblings such as baidu_upload (reverse direction) or file_download_url.

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?

Only says what it does, not when to choose it over baidu_upload, file_download_url, or the baidu_task_* family. No prerequisites (login/profile) or exclusions are given.

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