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

With no annotations provided, the description must disclose behavioral traits itself. 'Search' implies a read-only operation, but the description does not explicitly state it is non-mutating or describe the return format (e.g., list of document IDs, snippets). This leaves some uncertainty about what the tool actually does beyond searching, earning a middle score.

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

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

The description is two concise sentences, front-loaded with the primary action and purpose, followed by usage context. Every word adds value, with no redundancy or filler. It is well-structured and easy to scan.

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 (2 params, no output schema), the description covers the core purpose but does not mention what the search returns (e.g., document titles, links, or snippets). Without an output schema, this omission leaves a notable gap in completeness, but the tool is simple enough that the description 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?

Schema coverage is 100%, so both parameters are documented. The description adds value by giving concrete examples of query types (UI components, APIs, architectural guidance), which helps users formulate effective queries beyond the schema's generic description. This extra guidance raises the score above the baseline.

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

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

The description clearly states the tool's function as searching HarmonyOS/OpenHarmony documentation, with specifics on what can be found (UI components, APIs, architectural guidance). This distinguishes it from sibling tools like read_doc (reading a specific doc) and list_doc_topics (listing topics), making the purpose unambiguous.

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 indicates when to use the tool ('Use this to find UI components, APIs, or architectural guidance'), providing clear context for search-related tasks. It does not explicitly state when not to use it or mention alternatives, but the context is sufficient for basic selection among 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?

With no annotations provided, the description carries full behavioral disclosure burden. It implies a read-only operation ('List all') but does not explicitly mention safety, missing output details, or any restrictions. For a simple list tool, this is minimal but not 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 a single concise sentence that front-loads the action and then provides the purpose. Every word earns its place, and there is no redundant or vague phrasing.

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 zero-parameter tool with no output schema, the description covers the essential information: what is listed (documentation categories) and why (to understand the SDK structure). It could explicitly mention the return format, but 'List all...' sufficiently implies a list of categories.

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 is empty, so the baseline for parameter semantics is 4. The description adds context by clarifying the purpose and scope (categories of the HarmonyOS SDK), which goes 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 states a specific action ('List all available documentation categories') and identifies the resource (HarmonyOS SDK). It clearly distinguishes from sibling tools like find_docs and read_doc by focusing on the structural overview.

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

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

The description implies the tool is used to understand the SDK structure but does not explicitly contrast it with sibling tools or state when not to use it. No exclusions or alternatives are mentioned, leaving the decision 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?

With no annotations, the description must carry behavioral disclosure. It says 'Read' and 'full content', which conveys read-only behavior and non-truncation, but does not mention error handling, authentication, or any side effects. This is adequate but minimal for a simple read 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?

The description is a single concise sentence with no redundant or filler words. It front-loads the action ('Read the full content') and adds a clear purpose, making it easy to parse.

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 one-parameter, no-output-schema tool with no annotations, the description provides sufficient context to understand what the tool returns and why it exists. It could mention error behavior, but the combination of description and schema is largely complete for a simple read operation.

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 provides 100% coverage of the only parameter (objectId) and already notes it is obtained from find_docs. The description adds no additional parameter context beyond the broader purpose, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool reads the full content of a specific documentation file, with a specific purpose (code examples and detailed API usage). This distinguishes it from siblings like find_docs (search) and list_doc_topics (topics) by focusing on retrieving the full content for a known document.

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 detailed examples are needed, but does not explicitly name alternatives or exclusion criteria. The schema notes the ID comes from find_docs, but that is in the schema rather than the description. Thus, usage context is present but not fully explicit.

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