Search AiWiki

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 adds useful context about the content perspective (first-person) and query language flexibility (Chinese/English), but it omits details such as how results are ordered, whether search requires exact matches, or what variations in output might occur. The description is adequate but not deeply transparent about search behavior beyond the basic action.

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

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

The description is compact and front-loaded: it states the tool's purpose, domain, concrete use cases, and language flexibility in just two sentences. The parenthetical examples are efficient and informative without padding. Every element earns its place, making this an exemplary model of concise yet informative writing.

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 moderate complexity (4 parameters, no annotations, no output schema), the description provides strong domain context, examples of query topics, and language support. The schema already hints at return structure via the 'returned titles/summaries/urls' phrase in the lang parameter. However, the description could have explicitly tied to the sibling 'aiwiki_get_entry' for next steps, which would have made it fully complete. It covers most contextual needs without being exhaustive.

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 already provides 100% coverage for all four parameters (query, lang, limit, subject), so the baseline is 3. The description adds minimal parameter-specific meaning beyond the schema—it reiterates that queries can be Chinese or English, which duplicates the schema's query description. It does not introduce new parameter semantics or clarify parameter interactions, so the score stays at baseline.

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

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

The description opens with a specific verb and resource ('Search AiWiki') and immediately defines the resource as 'an encyclopedia of AI-coding pitfalls and LLM privacy protection'. This clearly distinguishes the search tool from its sibling 'aiwiki_get_entry' by scope (searching vs. retrieving) and content domain, making the tool's purpose unmistakable.

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 when to use the tool: 'Use when the user hits a recurring AI-coding failure... or an LLM privacy question...', with concrete examples. It does not explicitly list when-not-to-use or name the alternative 'aiwiki_get_entry', but the usage context is rich enough that an agent can infer the appropriate scenario. This is a clear context, though not a full when/when-not set.

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