Sibyl

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 mentions that the tool 'researches each item', implying external data gathering, but doesn't disclose behavioral traits such as data sources, accuracy limitations, processing time, rate limits, or authentication needs. For a research-intensive tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is appropriately sized and front-loaded, starting with the core purpose. Every sentence earns its place: the first defines the output, the second explains the research process and table format, and the parameter explanations are concise with helpful examples. No wasted words.

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 complexity (research-based comparison), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose, usage, and parameters well, but lacks details on behavioral aspects like research methodology or limitations. With output schema addressing returns, the main gap is in transparency.

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?

With 0% schema description coverage, the description fully compensates by explaining both parameters in detail. It specifies that 'items' should be 'comma-separated items to compare' with examples, and 'query' provides 'context for the comparison' with examples. This adds crucial meaning beyond the basic schema, clarifying format and usage.

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 ('generate', 'researches', 'produces') and resources ('structured comparison table', '2-5 items', 'markdown table'). It distinguishes from siblings by focusing on comparative analysis rather than individual analysis (analyze), data visualization (chart), or data retrieval (fetch_market_data, read_url).

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 clear context for when to use this tool ('for 2-5 items', 'to compare'), including examples of appropriate inputs. However, it doesn't explicitly state when not to use it or name specific alternatives among the sibling tools, though the purpose differentiation implies alternatives like 'analyze' for single items or 'chart' for visualizations.

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