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

No annotations are provided, so the description must carry full behavioral transparency. It lists what the log records but does not disclose side effects, idempotency, append-only nature, or whether it modifies existing logs. Key behavioral traits are missing.

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

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

The description is a single sentence that efficiently states the purpose and scope. It is front-loaded with the verb and key contents. Could be more structured with bullet points for clarity, but remains 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?

Given 13 parameters, no output schema, and no annotations, the description is too brief to provide complete context. It does not specify scope (per-session/project/user), required permissions, or return behavior. Important for an AI agent to use 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 31% (only roundType and outcome have examples). The tool description lists high-level categories but does not explain most parameters' meaning, structure, or constraints. For 13 parameters with low schema coverage, the description fails to compensate.

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

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

The description clearly states the tool appends an optimization log and lists the types of information recorded (user ideas, Codex decisions, skills referenced, file changes, verification results, safety boundaries). It distinguishes from siblings like local_mcp_read_optimization_log and local_mcp_optimization_log_status.

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

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

The description implies use after an optimization round but does not explicitly state when to use it vs alternatives, nor provide prerequisites or exclusions. The sibling tools suggest differentiation but description lacks explicit 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?

未提供注解，描述未说明工具是否具有副作用（如只读或修改）、是否需要网络或权限。虽然名称暗示它是建议性的，但未明确告知行为特性。

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?

描述仅一个句子，20字左右，极其简洁且关键信息前置（'基于...文档和...工程'，然后'输出...建议'）。无冗余。

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?

工具仅一个参数，无输出模式，无注解。描述未提及输出格式（如文本还是结构化），也未说明是否记录日志。对于简单工具，描述基本够用，但存在可改进之处。

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?

参数'target'在模式中已有明确描述 ('要优化的 MCP 名称')，描述未额外添加语义信息。模式覆盖率为100%，基线为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?

描述明确说明了工具的功能：基于本地文档和当前工程输出优化建议。动词'输出'和资源'优化建议'清晰，与同领域的 local_mcp_append_optimization_log 等兄弟工具区分开来。

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?

描述指出基于本地文档和当前工程，暗示了调用时机，但没有明确说明何时不应使用或有替代方案（如日志类工具）。缺少使用条件或排除说明。

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

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

No annotations are provided, so the description must disclose behavior. The verb '查看' implies a read-only action, but no explicit statement about non-destructiveness, authentication, or permissions. The description is minimal but adequate for a simple status query.

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

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

The description is a single sentence that conveys all essential information with no redundancy. It is front-loaded with the verb and resource.

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 adequately lists the return items. However, it could be more complete by noting whether the status is a single value or a list, or what format the path takes. Still, it covers the key points.

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

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

The input schema has zero parameters, so baseline is 4. The description adds meaning by specifying what the tool returns (status, path, record count, forced record rules), going beyond the empty schema.

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

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

The description clearly states the tool views status, path, record count, and forced record rules. The verb '查看' indicates a read operation. Among siblings, 'append' and 'read' are distinct, so it differentiates well.

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

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

The description implies this tool is for checking optimization log status versus reading logs (sibling local_mcp_read_optimization_log). However, no explicit when-to-use or when-not-to-use guidance is provided, leaving the agent to infer 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 provided, so description bears full responsibility. It mentions default behavior (last 10, Markdown) and read nature ('读取'), but lacks details on error handling, access restrictions, or rate limits. Adequate for a simple read operation, but could be more comprehensive.

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

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

Single sentence conveying purpose and default behavior without redundancy. Perfectly concise 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 no output schema and simple parameters, the description covers core functionality. It could mention that logs are in Markdown format, but the format parameter addresses that. Reasonably complete for a read tool.

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

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

Schema coverage is 100%, so the schema already documents limit and format. The description adds natural language defaults, but does not provide additional meaning beyond the schema. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool reads MCP optimization logs and defaults to the last 10 Markdown records. The verb '读取' (read) and resource 'MCP 优化日志' are specific, and it distinguishes from sibling tools like append, advice, and status.

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

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

No explicit guidance on when to use this tool versus alternatives. While siblings' names imply purposes, the description does not mention when not to use or provide exclusions. Usage context is implied but not clarified.

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

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

No annotations are provided, so the description carries full burden. It only states that the tool 'outputs' suggestions, implying a read-only operation, but does not disclose any behavioral traits such as side effects, required permissions, or data freshness. The lack of transparency is notable given 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 concise sentence that front-loads the core purpose. It avoids verbosity but could benefit from structured presentation (e.g., bullet points) for better readability, though it remains efficient.

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

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

Given the tool's simplicity (one optional parameter, no output schema, no annotations), the description provides the essential information about its function and filtering ability. However, it lacks details on output format or what 'skill routing' entails, leaving some gaps for a complete understanding.

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

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

Schema description coverage is 100% with one parameter 'topic' having a clear description in the schema. The description adds no additional meaning beyond what the schema already provides, meeting the baseline for high coverage.

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

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

The description clearly states the tool's function: outputting skill routing and usage suggestions based on installed skills, with optional topic filtering. It differentiates from sibling tools by focusing on skill routing for mini-program projects, though it does not explicitly contrast with specific 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 description implies usage when needing skill routing for mini-program projects based on installed Codex/Claude/agents skills, and the topic parameter suggests filtering use cases. However, no explicit guidance on when to use this tool versus alternatives or when not to use it.

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

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

No annotations provided, so description carries full burden. Mentions 'reading local rules' but does not disclose whether the tool modifies any state, auth requirements, or rate limits. Insufficient for a read operation.

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

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

Single sentence efficiently conveys purpose. No wasted words, but could be more structured for clarity.

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, but description lists output aspects. Lacks details on output format, side effects, or how the profile is constructed. Adequate but not thorough.

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?

One boolean parameter (includeSources) with full schema coverage. Description adds no extra meaning beyond schema, so 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?

Description clearly states it reads local rules and produces a work profile covering communication, delivery, security, knowledge base, and coding habits. Distinguishes from siblings, none of which provide a user profile.

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

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

No explicit guidance on when to use this tool versus alternatives. Does not mention prerequisites, exclusions, or 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?

With no annotations provided, the description should fully disclose behavior. It states the output (guide and boundaries) but does not explicitly confirm the tool is read-only or mention any side effects. The description is adequate but not fully explicit.

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. It efficiently conveys the action and subject matter.

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

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

Given the tool's simplicity (no parameters, no output schema, clear purpose), the description fully communicates what the agent should expect: a combination usage guide and security boundaries. No additional context is needed.

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

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

The tool has zero parameters, so baseline is 4. The description does not need to add parameter information, and it correctly omits any param details.

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 outputs a combined usage guide and security boundaries for CloudBase MCP and local miniapp engineering consultant MCP, specifying the verb '输出' and the resource (guide and boundaries). It distinguishes itself from sibling tools by its unique focus on guidance.

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

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

The description provides no information about when to use this tool versus alternatives, lacks any context about prerequisites or conditions, and offers 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?

Without annotations, the description carries full burden but only states it 'generates a checklist'. Does not disclose if it modifies state, side effects, or what the output contains. No output schema available, leaving agent uninformed about tool 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?

Single sentence is concise and covers main purpose. However, it could be more structured (e.g., bullet list of actions) for clarity.

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 6 optional parameters and no output schema, the description lacks detail on return value, parameter dependencies, or workflow context. Incomplete for a tool likely involved in critical release steps.

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 parameter descriptions. Description adds no additional semantic value beyond listing the action types implicitly. Baseline 3 is appropriate.

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

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

Description clearly states the tool generates a preflight checklist for specific actions (cloud function deployment, miniapp upload/audit/release, npm/github sync) to avoid common errors. Distinguishes from sibling tools like 'miniapp_launch_checklist' by being release-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?

Implies use before executing the listed actions, but provides no when-not-to-use guidance or comparison to similar tools like 'miniapp_launch_checklist'. Lacks explicit usage context.

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

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

With no annotations, the description should cover behavioral traits. It does not mention if the tool is read-only, what output format is returned (e.g., raw Mermaid text or a file), or any side effects like modifying files. The phrase 'generate' implies creation but without safety 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?

Single sentence conveying the core purpose and entities involved. No redundancy; every word is necessary.

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 and no output schema, the description should explain what the generated diagram looks like, how it's delivered, and error scenarios. It is too brief for a tool with multiple inputs and no explicit output details.

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

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

Schema description coverage is 75%, so baseline is 3. The description adds the context of 'Mermaid' but does not elaborate on parameter specifics like how target or featureName are used (e.g., filtering, highlighting). The description adds minimal extra value beyond the schema.

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

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

The description clearly states the tool generates a Mermaid dependency diagram for specific entities (pages, files, routes, cloud functions, controllers, collections), providing a specific verb and resource. It distinguishes from siblings like miniapp_project_map or miniapp_graph_stats by focusing on dependency relationships.

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 vs. alternatives like miniapp_understand_project_flow or miniapp_graph_stats. No context on prerequisites (e.g., project must exist) or when not to use it.

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

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

No annotations are provided, so the description must disclose behavioral traits. It describes a read-only generation of a recovery manual, but does not mention any side effects, permissions needed, or return format. Minimal information beyond the basic function.

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 that efficiently conveys the tool's purpose and scope. Every word earns its place with no redundancy.

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

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

The tool has no output schema, so the description should clarify the output format. While it describes the generated manual's coverage, it does not specify whether it returns plain text, markdown, or JSON. Context is mostly complete given the sibling tools landscape.

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

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

Schema coverage is 100%, and the description adds no extra semantic beyond the schema's parameter descriptions. The description merely restates that topic filters by issue type and includeCaseStudy controls summary inclusion.

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

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

The description clearly states the tool's function: compiling common WeChat mini-program faults into a recovery manual. It specifies the covered topics (session confusion, missing page files, etc.), making it distinct from sibling tools like miniapp_launch_checklist or miniapp_security_quick_scan.

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

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

The description implies usage for troubleshooting common faults but does not explicitly state when to use this tool over alternatives. No exclusions or when-not-to-use guidance is 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 bears full responsibility for behavioral disclosure. It only states the action (query) without revealing side effects, authentication requirements, rate limits, or return format. This is insufficient for safe agent invocation.

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 with no wasted words, front-loaded with the action. It is concise and efficiently communicates the tool's purpose.

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

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

Given the tool has one parameter, no output schema, and no annotations, the description is minimally adequate. It explains the purpose but lacks details about return values, behavior, or prerequisites that would make it fully complete for an agent.

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?

Although schema coverage is 100% (parameter description provides examples), the tool's description adds meaning by explaining that the topic is used to query specific resources (docs, GitHub projects, tool indexes). This provides context beyond the schema's list of example values.

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 queries locally organized mini-program documentation, GitHub projects, and engineering tool indexes by topic, using a specific verb and resource. It distinguishes from sibling tools like miniapp_cloudbase_mcp_guide or miniapp_dependency_diagram that have different purposes.

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

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

The description does not provide any guidance on when to use this tool versus alternatives. It only states what it does implicitly, with no explicit when-to-use, when-not-to-use, or alternative tool references.

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 exist, so description must disclose behavioral traits. It only states output concept but not technical behavior: whether it modifies files, returns data, requires permissions, or has side effects. Critical gaps for a generation 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?

Single sentence is concise but not structured; lacks parameter breakdown or formatting. For a tool with 4 parameters, the description could be enhanced with bullet points or hints while remaining 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?

Complex tool (generating blueprint with multiple components) but description is minimal. No output schema, no explanation of what 'blueprint' entails, no mention of limitations or dependencies. Insufficient for agent to fully understand 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 coverage is 0% and description adds zero meaning to any of the 4 parameters (productName, brandName, depth, linkExistingProject). No explanation of what each parameter does or how to use them.

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

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

Description uses specific verb 'generate' and resource 'engineering blueprint for WeChat Mini Program product', detailing coverage from positioning to launch. Clearly distinguishes from sibling tools which focus on analysis/optimization of existing projects.

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 vs alternatives, no prerequisites or exclusions mentioned. The description does not help the agent decide context for invocation.

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 only says 'output,' suggesting a read-only operation, but it does not explicitly state it has no side effects, permission requirements, or other behavioral traits. This leaves room for ambiguity.

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

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

The description is a single concise sentence that front-loads the main action and output. It is efficient but lacks any additional context that might be helpful.

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 lists output content types but omits details about return format, use cases, or when to invoke the tool. Given no output schema, more context would be beneficial.

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 50% (only 'limit' has a description). The description does not explain any parameters, so it adds no value beyond what the schema already provides. The undocumented 'projectPath' parameter is not clarified.

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 outputs statistics of a lightweight code graph, listing specific content types (node/edge types, route links, important nodes, risk tips). While it doesn't explicitly differentiate from sibling tools like miniapp_dependency_diagram, the focus on statistical summary distinguishes it implicitly.

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

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

The description implies usage when a statistical summary of the code graph is needed, but it does not provide explicit guidance on when to prefer this tool over siblings or when not to use it.

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

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

Annotations are absent, so the description must disclose behaviors. It mentions reporting status but also has a writeCache parameter that modifies local cache—a side effect not explicitly stated. The description implies read-only reporting but allows writes, lacking full 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 dense sentence that packs key information. It could be more structured (e.g., separate output description), but it is concise and front-loaded with purpose.

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

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

The tool has 3 parameters and no output schema. The description does not explain the return format, what 'safe text files' means, or the implications of writeCache=true. This leaves gaps for an AI agent to fully understand the tool's behavior and results.

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 67%: limit and writeCache have clear descriptions, but projectPath lacks one. The overall description does not add parameter meaning beyond the schema. Baseline 3 is appropriate given moderate coverage.

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

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

The description states it computes hashes of safe text files and reports status changes relative to local cache, using CodeGraph incremental indexing. This is specific enough to distinguish from sibling tools that inspect projects or scan for security, though 'safe text files' is ambiguous.

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 miniapp_security_quick_scan or miniapp_inspect_project. The description only explains what it does, not when to invoke it.

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

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

No annotations are provided, so the description carries the full burden. It states what the tool does (scan and output) but does not disclose whether it modifies anything, required permissions, or performance implications. The description is moderately transparent but lacks details on side effects or assumptions.

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

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

The description is a single concise sentence that conveys the main purpose. It is front-loaded and efficient, though slightly more structure (e.g., listing inputs and outputs separately) could improve clarity.

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 two optional parameters and no output schema, the description lists the key outputs (pages, tabBar, cloud functions, etc.), providing reasonable completeness. The scope of the tool is clear, though the return format is not 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 baseline is 3. The description does not add parameter-specific context beyond what the schema already provides. The tool parameters (projectPath, includeReadme) are adequately explained in the schema.

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

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

The description clearly states the verb 'scan' and the resource 'local WeChat mini-program project', listing specific outputs (pages, tabBar, cloud functions, business modules, suggestions). It is specific and distinguishes from sibling tools by focusing on inspection.

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

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

The description implies usage for inspecting a mini-program project but provides no explicit guidance on when to use this tool versus alternatives like miniapp_security_quick_scan or miniapp_project_map. No when-not-to-use or alternative mentions.

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 only states it generates a checklist, but does not disclose side effects (e.g., if it modifies anything), output format, or prerequisites. For a non-mutating tool, safety is implied but not explicit.

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

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

The description is a single sentence that efficiently conveys the tool's purpose and scope. No unnecessary words or repetitions.

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

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

Given the simplicity of the tool (one optional parameter, no output schema), the description covers the main areas but lacks details like checklist format, whether output is text or list, and how the parameter affects the checklist. It is minimally adequate but could be more complete.

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

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

Schema description coverage is 0%, so the description must explain parameters. It mentions 'customer private album delivery' which relates to the 'includePrivateAlbum' parameter, but does not explain the parameter's effect or default behavior. This is insufficient for the agent to understand the parameter's role.

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 'generate a check list before launching a WeChat mini program' and lists specific areas covered (cloud development, privacy, review, customer private album delivery). It uses a specific verb and resource, and distinguishes from sibling tools like miniapp_security_quick_scan which focuses on security.

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, nor when not to use it. The description only explains what it does without providing context or exclusions.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states it 'generates a map' implying a read operation, but does not mention permissions, resource usage (e.g., scanning many files), or whether it modifies the project. The agent cannot determine side effects or 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 description is a single sentence, concise and front-loaded. It begins with a reference to Understand-Anything which, while informative, adds slight overhead. Overall, it is efficient and to the point.

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

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

Given no output schema, the description should explain return values, but it only lists components ('pages, files, cloud functions, collections, and dependency edges'). The format parameter covers output format. However, the description lacks scope, performance implications, and explicit read-only nature. It is adequate but not comprehensive for a tool with 4 parameters and many 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 coverage is 100% with each parameter having a description. The tool description adds high-level context (knowledge graph approach, types of elements) but does not provide additional meaning beyond the schema for any parameter. Baseline 3 is appropriate as the schema already documents what each parameter does.

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 generates a project map with specific components (pages, files, cloud functions, collections, and dependency edges) using a knowledge graph approach. It differentiates from siblings by mentioning a broader set of elements, but does not explicitly distinguish from similar tools like miniapp_dependency_diagram.

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 usage guidance is provided. The description does not indicate when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. This forces the agent to infer context from the tool name and parameters.

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 cover behavioral traits. It fails to mention whether the tool has side effects, requires specific permissions, or any limitations. The 4-tier structure is introduced but not explained, leaving uncertainty about what the tool actually does.

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 lacks necessary details. It front-loads the core idea but is not fully self-contained, requiring the user to infer additional 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?

With 7 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the four tiers, output format, or how to interpret results. The tool's complexity demands a richer description.

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 baseline is 3. The description does not add meaning to individual parameters beyond what the schema provides; it only mentions 'task' which ties to query/goal/featureName. No additional parameter semantics are offered.

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 outputs a 4-tier context (Core/Near/Extended/Background) for tasks, specific to miniapp engineering. However, it does not differentiate from sibling tools like miniapp_inspect_project or miniapp_project_map, which may also provide context.

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

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

The description implies usage for task-based context retrieval ('按任务输出') but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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 full behavioral disclosure burden. It lists checked areas but does not specify if the tool is read-only, whether it modifies state, requires special permissions, or how results are processed. 'Quick scan' lacks behavioral detail.

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

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

Single sentence in Chinese, efficient and front-loaded. No fluff; every part contributes to understanding the tool's core function.

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

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

Given no output schema and no annotations, the description omits critical context: output format, side effects, prerequisites (e.g., project must exist), and whether results persist. The tool appears complex but is underexplained.

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 has three parameters with 67% description coverage. The description mentions '扫描多少个安全文本文件' (how many security text files to scan) indirectly explaining 'limit', and uses '最多返回多少条发现' (max findings) for 'maxFindings'. However, 'projectPath' lacks context beyond the tool's purpose, so description adds moderate value.

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

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

The description clearly states the tool's purpose: a security quick scan for mini-program launch, checking specific security aspects like keys, sensitive logs, permissions, etc. It distinguishes itself from sibling tools by focusing solely on security scanning, using the verb '检查' (check).

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

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

No explicit guidance on when to use this tool versus alternatives. The description implies pre-launch usage but does not mention exclusions or alternative tools for different security needs. Among siblings, tools like 'miniapp_launch_checklist' or 'miniapp_inspect_project' exist without differentiation.

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

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

No annotations are provided, so the description bears full responsibility. The description indicates the tool outputs a roadmap but does not disclose whether it modifies data, requires authentication, or has side effects. The verb '输出' suggests a read-only operation, but this is not explicit.

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

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

The description is a single, concise sentence that covers the tool's purpose and key output components. No unnecessary words; front-loaded with action and resource.

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 lists output components but does not explain the output format (e.g., text, JSON, checklist) or error handling. Given no output schema, more detail on what the agent can expect would be helpful. Sibling tools are planning-related, so context is moderate.

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

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

All parameters have descriptions in the schema, so baseline is 3. The tool description does not add meaning beyond the schema; it lists roadmap components but does not explain how parameters like 'depth' or 'phase' affect the output. Parameter semantics are adequately covered by the schema.

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

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

The description clearly states the tool outputs an executable roadmap for mini-program showcase, listing specific components like business positioning, MVP boundary, etc. It uses a specific verb '输出' and resource '路线图', but does not explicitly distinguish from sibling tools like miniapp_generate_blueprint or miniapp_launch_checklist.

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

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

The description implies use for beginners ('小白可执行') but provides no explicit guidance on when to use this tool versus alternatives. No exclusions or conditions are 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?

No annotations are present, so the description must fully disclose behavior. It only mentions analysis of impacts but does not state side effects, authorization needs, or whether it is read-only. The description is too vague to understand behavioral traits.

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

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

The description is a single concise sentence that front-loads the purpose. It is appropriately sized for a simple tool with three parameters, though it could benefit from slight structuring.

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

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

Given the complexity of analyzing impacts across multiple dimensions (pages, cloud functions, etc.) and the absence of an output schema, the description does not convey what the analysis produces. The agent is left uninformed about the tool's output format or structure.

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 67%. The description adds value for featureName by providing concrete examples (客户成片展示等) and for limit by stating the default and interpretation (命中文件). This goes beyond the schema, though projectPath lacks any description.

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

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

The description clearly states the verb 'analyze' and the resource 'feature name', listing specific impact areas (pages, cloud functions, etc.). This distinguishes it from sibling tools like miniapp_understand_file_role, though it does not explicitly differentiate.

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 usage context, when-not to use, or alternatives are provided. The description only states what the tool does, leaving the agent without guidance on choosing this tool over siblings.

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

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

No annotations are present, so the description must fully disclose behavioral traits. It does not mention whether the tool reads files, requires network access, has side effects, or any limitations. The description is too brief to provide adequate 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 concise sentence that directly states the tool's function. It is front-loaded with the core purpose and contains no redundant or irrelevant information.

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

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

No output schema exists, so the description should clarify the return format or structure. It mentions explaining role, clues, and next steps, but does not specify how this information is presented (e.g., text, structured data). Given the complexity of the domain and many sibling tools, the description is insufficiently 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 67% (2 of 3 params described). The tool description adds no parameter-specific information; it does not explain the missing 'projectPath' parameter or add meaning beyond the schema for existing ones. The description fails to compensate for the schema's gaps.

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 action (explain), the resource (file role in a WeChat Mini Program project), and the output (upstream/downstream clues and next steps for beginners). It distinguishes from sibling tools like miniapp_understand_feature_impact and miniapp_understand_project_flow by its specific focus on file roles.

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

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

The description provides no guidance on when to use this tool over alternatives, no exclusion conditions, and no context for when it is appropriate. It only states what the tool does, leaving the agent to infer usage 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 must bear full burden. It only states that the tool 'explains', but the input schema implies it scans files (via projectPath and limit). This behavioral trait (file scanning) is not disclosed, and no side effects or permissions are mentioned, leading to low 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 extremely concise, consisting of a single sentence that front-loads the purpose. Every word serves a function. However, it could be slightly expanded to include behavioral context without becoming verbose, so it is not perfect but reasonably 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?

Without an output schema and with minimal description, the tool's behavior is underspecified. The description does not explain how the tool uses the input parameters, what the output looks like, or what 'scanning' entails. For a tool targeting beginners, this lack of context significantly reduces completeness.

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

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

The description adds no meaning beyond the input schema. While schema coverage is 67% (two parameters have descriptions), the description does not clarify the purpose of projectPath or how the parameters relate to the explanation process. The goal and limit descriptions are already in the schema, so the description adds no 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 what the tool does: explain the complete engineering process of a mini-app from requirements to launch. It uses specific verbs ('解释' meaning explain) and resources ('完整工程流程' meaning complete engineering process), differentiating it from sibling tools that focus on specific aspects like feature impact or file roles.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., miniapp_understand_feature_impact, miniapp_work_breakdown), explicit usage context is missing, leaving the agent to guess based solely on the name and description.

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

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

With no annotations, the description must disclose behavioral traits. It only states the output is task lists but omits whether it modifies data, requires permissions, or has side effects. Critical behavioral context is missing.

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. While efficient, it lacks essential details about parameters and output, making it insufficiently 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?

Given the lack of output schema and schema descriptions, the description is severely incomplete. It fails to clarify parameter usage, return format, or behavioral context, leaving the agent underinformed.

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

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

Schema description coverage is 0%, and the tool description does not explain any parameters. The 'featureName' and 'phase' parameters have no added meaning beyond their types and enum values.

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: breaking down a feature into six task categories (requirements, UI, frontend, backend, QA, launch). It uses a specific verb and resource, and distinguishes from sibling tools that focus on other aspects like blueprint generation or security scans.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, context, or exclusions, leaving the agent without decision support.

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. The description mentions 'read' but omits the safety gate: the confirmed parameter must be true to execute. This critical behavioral trait (default false, no read without confirmation) is not disclosed in the description.

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

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

The description is a single sentence in Chinese, concise and front-loaded with the action. No wasted words, but could be more structured with additional contextual detail.

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

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

Given no output schema, no annotations, and a moderate number of siblings, the description is incomplete. It lacks usage guidance, behavioral nuance (confirmation), and details about the returned context format.

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 50% (only confirmed described). The description itself does not explain parameters beyond what the schema provides. The query parameter lacks description but the tool name implies it's the search query. Baseline 3 due to moderate coverage; no additional value added.

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

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

The description clearly states the action: calling a local knowledge base route search to read context related to the current mini-program/business. It specifies verb and resource, but does not differentiate from sibling tools like miniapp_relevant_context or miniapp_docs_lookup.

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. The description implies it is for reading context, but does not specify scenarios where it is preferred over other context-related tools.

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