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

No annotations are provided, so the description carries full burden. It discloses auto-detection of log paths, fallback to manual path, and supported frameworks. However, it does not mention any side effects or authentication needs, but for a read-only tool this is acceptable. Clarity on limitations (no HTTP logs) adds transparency.

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

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

The description is a single coherent paragraph that front-loads the purpose, then lists use cases, exclusions, and framework support. While comprehensive, it could be slightly more concise; however, every sentence contributes 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?

The description covers purpose, usage, and parameters well, but without an output schema, it lacks details about the return format (e.g., raw log lines, timestamps). It also doesn't mention file size limits or handling of large files. This gap reduces completeness for a tool with four parameters.

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%, but the description adds significant value: explaining the relationship between site_name and log_path, the framework enum behavior, and the fallback logic. This goes beyond the schema and aids correct invocation.

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

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

The description clearly states the tool reads application logs (business/program records) and explicitly distinguishes from get_nginx_logs by noting it does not include HTTP request logs. The verb '读取' (read) and resource '业务日志' (business logs) are specific.

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

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

Explicit guidance on when to use (troubleshooting SQL errors, interface exceptions, business logic errors, etc.) and when not to (HTTP logs, which should use get_nginx_logs). This provides clear context for tool selection.

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

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

The description states '只读，不修改' (read-only), but the input schema allows a 'save' action that modifies the config file. This is a direct contradiction. Annotations are absent, so the description carries full burden but is misleading.

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

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

The description is very concise (two short sentences) and front-loaded with the core purpose. However, it omits the save functionality, which makes it incomplete; but for what it covers, it 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?

No output schema, and description does not explain return values or error conditions. More critically, it fails to describe the save action, leaving the tool's full behavior undocumented. Schema compensates for parameters but not for behavioral 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?

Input schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond schema; it does not elaborate on parameters or their usage.

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

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

The description clearly states it reads Nginx config for a specific site, and specifies the file path. It distinguishes from siblings by being specific to Nginx config. However, the claim '只读，不修改' (read-only) contradicts the schema which includes a 'save' action, reducing clarity.

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 says it is suitable for viewing reverse proxy, SSL, location rules, implying when to use. It does not mention when not to use or alternatives, but siblings are distinct (logs, system status, etc.), providing implicit context.

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

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

No annotations are provided, so description carries full burden. It discloses automatic log path detection ('自动在 /www/wwwlogs/ 目录探测日志路径'), lists recorded fields, and clarifies scope (Nginx layer only). The behavior is clearly described without contradictions.

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 longer than necessary but well-structured: starts with purpose and fields, then use cases, then limitations and auto-detection. It could be more concise by removing repetition from schema descriptions, but it remains clear and front-loaded.

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

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

Given 4 parameters, no output schema, and siblings focusing on other log types, the description adequately explains what logs contain (fields listed), when to use, and limitations. It does not detail the exact return format, but the listed fields provide sufficient context. Lacks mention of error log message structure, but overall complete for typical use.

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

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

Schema coverage is 100%, baseline 3. The description adds value by explaining auto-detection of log paths and providing context (e.g., '无需手动指定路径') beyond schema descriptions. However, some schema info is repeated (e.g., default values). The added context justifies a score of 4.

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

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

The description clearly states it reads Nginx access/error logs and lists specific fields (IP, time, URL, status code, etc.). It explicitly distinguishes from application logs and alternative siblings like get_app_logs by stating it does not include business logic or database info. The verb '读取' and resource 'Nginx层日志' are specific and non-tautological.

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

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

The description provides explicit use cases: HTTP status code anomalies, traffic analysis, crawler/attack identification, Nginx config issues, static resource 404s. It also clearly states what the tool does not cover ('不包含任何业务逻辑、数据库、接口报错等应用层信息'), implicitly guiding users to get_app_logs for application-level issues. This is explicit when-to-use and when-not-to-use.

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

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

The description indicates a read-only operation (reading logs) without contradictions, as there are no annotations. It provides some behavioral context (examples of log types) but does not disclose potential side effects, permissions, or limitations beyond that.

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 in Chinese, efficiently conveying purpose and examples. It is well front-loaded but could benefit from slightly more structure, such as separating use case from examples.

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

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

For a simple tool with one parameter and no output schema, the description covers essential information: what logs are retrieved and an auditing use case. The sibling tools provide context, making the description fairly 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?

The input schema already provides a complete description of the 'limit' parameter, including default and range. The description does not add additional meaning beyond what the schema conveys, so a baseline score of 3 is appropriate.

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

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

The description clearly states it reads Baota panel operation logs, listing specific examples like login records, configuration changes, and software installations. This precisely identifies the tool's function and distinguishes it from sibling tools like get_app_logs or get_nginx_logs.

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 mentions the tool is suitable for auditing who operated the panel and when, providing a clear use case. However, it does not explicitly state when not to use it or compare it to alternatives, leaving some inference 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. It discloses the tool is real-time and lists returned metrics, but does not mention auth requirements, rate limits, or any potential side effects. The disclosure is adequate for a simple read-only 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 concise sentences, front-loaded with purpose and followed by usage context. No wasted words.

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

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

For a tool with no parameters and no output schema, the description sufficiently explains what it returns (CPU, memory, disk, network, load) and its use case. No missing information.

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

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

The tool has zero parameters, so schema coverage is 100%. The description adds value by listing the specific metrics returned, which is not in the schema. Baseline 4 is appropriate.

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

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

The description clearly states it retrieves real-time server status listing specific metrics (CPU, memory, disk, network, system load). It distinguishes itself from sibling tools that handle logs or configs.

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 explicitly states it is suitable for troubleshooting performance issues or confirming resource sufficiency, providing clear context for when to use it. It does not explicitly mention when not to use, but the context is sufficient.

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

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

No annotations provided. The description fails to disclose that the tool can create and delete backups, only describing the list behavior. This is a significant omission and potentially misleading for an AI agent.

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

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

The description is a single sentence, but it is underspecified. It omits crucial information about the other actions, making it not appropriately sized for the tool's actual functionality.

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?

No output schema, no annotations, and the description only covers one of the three possible operations. The tool requires more context to be used correctly, such as when to use each action and what the response looks like.

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

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

Schema description coverage is 100%, and the schema already provides detailed descriptions for all parameters including the action enum. The description adds no additional semantic value beyond what is in the schema.

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

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

The description only mentions querying the backup list, but the input schema includes 'create' and 'delete' actions. This is misleading as the tool performs multiple operations. The description does not accurately represent the full purpose.

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

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

No guidance on when to use which action (list, create, delete) or how to choose among them. No alternatives mentioned despite sibling tools being available.

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, and the description fails to disclose behavioral traits such as side effects of add/delete actions, required site_name validity, or that the tool modifies state beyond querying.

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

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

The description is a single sentence, which is concise, but it omits the add/delete functionality entirely, making it incomplete. The sentence earns its place only partially by listing output attributes.

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 4 parameters and 2 required, with no output schema and no annotations, the description should explain the different action modes and prerequisites. It only covers the 'list' case, leaving add/delete behavior underspecified.

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

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

The input schema covers all parameters with descriptions (100% coverage). The description adds value by specifying output fields (domain, port, addition time) not present in the schema, though it does not elaborate on the action parameter beyond its enum.

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 'query list of all domains bound to the website' which matches the tool name 'list_domains', but the input schema reveals the tool can also add and delete domains, which is not mentioned. This creates ambiguity about the tool's full purpose.

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

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

No guidance on when to use this tool versus sibling tools (e.g., list_sites, get_nginx_config). The action parameter provides options but no contextual advice on appropriate usage.

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

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

The description discloses the return content (domain, root directory, running status). Since no annotations are provided, the description carries the burden, and it adequately describes what the tool does. However, it does not mention any potential side effects or limitations, though for a read-only list tool this is sufficient.

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

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

The description is concise: two sentences, no filler. The first sentence states purpose and output, the second gives usage guidance. Every word earns its place.

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

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

Given the tool has no output schema, the description adequately specifies the return fields (domain, root directory, running status). The search parameter behavior is fully explained. For a simple list tool with one optional parameter, the description is complete and actionable.

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

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

The input schema describes the 'search' parameter as '按网站名称或域名模糊搜索' (fuzzy search by name or domain). The description adds '不填则返回所有网站' (if left blank, returns all sites), which clarifies default behavior beyond the schema. With 100% schema description coverage, the baseline is 3, and the added detail justifies a 4.

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

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

The description clearly states the tool's purpose: '列出宝塔面板中所有托管的网站，包括域名、根目录、运行状态。' (List all hosted websites in BT panel, including domain, root directory, running status.) It distinguishes from siblings like list_domains by specifying the included fields.

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

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

The description provides explicit usage guidance: '查询日志前先用此工具确认网站名称和路径。' (Before querying logs, use this tool to confirm website name and path.) This tells the agent when to use this tool, adding contextual value.

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 discloses it is read-only and warns about large files, but does not cover other behavioral aspects like permissions, error handling, or file size limits.

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

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

The description is extremely concise with two sentences that front-load the purpose, examples, and a key recommendation—no wasted words.

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

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

The description is fairly complete given the simple tool: it covers purpose, usage examples, and a warning. However, it lacks details about error handling or return format, and could better address sibling tool differentiation.

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

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

Schema coverage is 100% with descriptions for both parameters; the tool description adds a recommendation to use last_lines, but the schema already fully explains parameter meanings, so minimal 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 clearly states it reads any file content (read-only) and provides specific use cases like config files and log paths, distinguishing from sibling tools that focus on specific logs or listings.

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 clear context for when to use (viewing config files, custom logs) and recommends using the last_lines parameter for large files, but does not explicitly state when not to use or mention alternatives among siblings.

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