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

With no annotations provided, the description carries full burden for behavioral disclosure. It describes the core functionality (fetching, parsing, extracting links) and output structure (document content, type information, discovered links), but lacks details about error handling, rate limits, authentication requirements, or performance characteristics. The description adds value beyond what's in the schema but doesn't provide comprehensive behavioral context.

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

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

The description is perfectly concise with three sentences that each earn their place: first states the core functionality, second establishes the exclusive usage context, third specifies the return values. No wasted words, front-loaded with the most important information about what the tool does.

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

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

For a single-parameter tool with no annotations and no output schema, the description provides adequate context about functionality and usage boundaries. However, it lacks details about the return format structure, error conditions, or what constitutes 'ANP 文档' versus other URLs. The description is complete enough for basic understanding but has gaps for comprehensive tool usage.

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

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

The schema description coverage is 100% with the single 'url' parameter well-documented in the schema. The description doesn't add any parameter-specific information beyond what the schema already provides about the URL parameter. This meets the baseline of 3 when the schema does the heavy lifting for parameter documentation.

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 with specific verbs ('抓取并解析' - fetch and parse) and resource ('ANP 文档' - ANP document), and distinguishes it from siblings by explicitly stating it's the '唯一允许方法' (only allowed method) for accessing URLs in the ANP ecosystem. This provides clear differentiation from 'anp.invokeOpenRPC' and 'anp.setAuth' which have different functions.

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 by stating this is the '唯一允许方法' (only allowed method) for accessing URLs in the ANP ecosystem, creating a clear boundary for when to use this tool versus alternatives. It establishes this as the mandatory approach for ANP document access, though it doesn't specify when NOT to use it for non-ANP URLs.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the protocol (JSON-RPC 2.0) and that it handles '结构化交互' (structured interactions), it lacks critical behavioral details: authentication requirements, error handling, rate limits, whether it's idempotent, or what the response format looks like. For a tool that makes remote calls, this is a significant gap.

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

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

The description is appropriately concise with two sentences that convey the core functionality. The first sentence states the purpose clearly, and the second adds context about interacting with ANP agents. There's no wasted text, though it could be slightly more front-loaded with the most critical information.

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

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

Given the complexity of making JSON-RPC calls, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, authentication needs, or provide examples of typical usage. For a 4-parameter tool that performs remote procedure calls, this leaves too many unknowns for effective agent use.

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

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

Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it doesn't explain how parameters should be structured, provide examples, or clarify relationships between parameters. The baseline of 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: '使用 JSON-RPC 2.0 协议调用 OpenRPC 端点上的方法' (invoke methods on OpenRPC endpoints using JSON-RPC 2.0 protocol). It specifies the verb ('调用' - invoke) and resource ('OpenRPC 端点上的方法' - methods on OpenRPC endpoints), but doesn't explicitly differentiate from sibling tools like anp.fetchDoc or anp.setAuth, which appear to 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 provides minimal usage guidance. It mentions '此工具处理与暴露 OpenRPC 接口的 ANP 智能体的结构化交互' (this tool handles structured interactions with ANP agents exposing OpenRPC interfaces), which gives some context about when to use it, but offers no explicit guidance on when to choose this tool versus alternatives like anp.fetchDoc or anp.setAuth, nor any prerequisites or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it establishes authentication context that persists for subsequent calls, specifies the credential sources (local DID document and private key files), and indicates this is a setup/configuration operation rather than a data operation. However, it doesn't mention potential side effects like error conditions or what happens if authentication fails.

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 and well-structured in just two sentences. The first sentence states the core purpose, and the second sentence explains the usage context and benefit. Every word serves a clear purpose with zero wasted information, making it easy for an AI agent to parse and understand.

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 2-parameter authentication setup tool with no annotations and no output schema, the description provides excellent context about what the tool does and how it integrates with sibling tools. It clearly explains the tool's role in the authentication flow. The only minor gap is the lack of information about return values or error conditions, but given the tool's straightforward nature, this is acceptable.

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

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

The schema has 100% description coverage, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. This meets the baseline of 3 when schema coverage is high, but doesn't provide additional semantic context about how these parameters interact or their format requirements.

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 with specific verbs ('设置 DID 认证上下文', '建立认证') and identifies the resource (authentication context). It explicitly distinguishes from sibling tools by mentioning that subsequent calls to 'fetchDoc' and 'invokeOpenRPC' will automatically use these credentials, establishing clear differentiation.

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: it specifies when to use this tool ('使用本地 DID 文档和私钥文件建立认证') and names the specific sibling tools ('fetchDoc' and 'invokeOpenRPC') that will benefit from this authentication setup. This creates clear context for when this tool should be invoked versus when to use the sibling tools directly.

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