search_lwn

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains it searches titles and body, allows filtering by subsystem and limit, and returns a dictionary with 'articles' and 'evidence_sources'. However, it does not disclose potential rate limits, authentication needs, or pagination behavior, which for a read-only search tool might be acceptable but is not richly transparent.

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 structured into summary, args, and returns sections, with no wasted words. It is somewhat verbose with the 'Args:' block, but every sentence provides necessary information. The front-loaded summary immediately conveys the core 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's moderate complexity (3 params, one required, an output schema), the description covers all essential aspects: purpose, parameter semantics, and return format. It lacks details like sorting or pagination, but for a search tool this is sufficient for correct selection and invocation. The presence of an output schema reduces the need to explain return values in detail.

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 compensate, and it does thoroughly. Each parameter is explained: 'query' (keywords), 'subsystem' (optional filter with examples), and 'limit' (max articles). This exceeds schema info, giving full semantic clarity for all parameters, including defaults and nullability.

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 ('Search') and the resource ('Linux Weekly News (LWN) articles on kernel development'), making the tool's purpose unambiguous. It distinguishes itself from sibling tools like search_lkml (mailing list) and get_lwn_article (specific article retrieval) by using the verb 'search' and specifying the LWN domain.

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 when to use the tool (when searching LWN articles) but provides no explicit exclusions or references to alternatives. It doesn't say 'use search_lkml for mailing list posts' or 'use get_lwn_article to fetch a specific article,' leaving the agent to infer the appropriate context from the tool name and sibling list.

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