search_and_summarize

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

With no annotations provided, the description carries the behavioral disclosure burden. It does well by disclosing the internal pipeline (search, rerank, fetch, synthesize), the use of a local LLM (qwen3:14b), and the fallback to raw fetched content when Ollama is unavailable. It stops short of describing latency, failure modes beyond the fallback, or any side effects, but covers the most important behavioral traits.

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?

Three sentences with no filler: the pipeline is front-loaded, the return nature and fallback are stated, and the recommended usage closes the description. Every sentence adds distinct value and the length is appropriate for the tool's complexity.

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?

The description is fairly complete for a research/synthesis tool: it covers the process, output style, fallback behavior, and best-case use. Because there is no output schema, the description's mention of 'structured answer with source attribution' is useful, though it leaves exact citation format and error behavior unspecified. Given the parameter schema handles the 9-parameter detail, this is a reasonable level of completeness.

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 baseline is 3 and the description does not need to repeat parameter details. The description adds context about what happens to fetched top results but does not elaborate on parameters like fetch_count, engines, or site. This is acceptable given the schema already documents every parameter.

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 names a precise multi-step action ('Search, rerank, fetch top results, then synthesize a summary with citations') and a specific deliverable ('structured answer with source attribution'). It also distinguishes itself from raw-page tools by explicitly stating it returns pre-digested synthesis rather than raw pages.

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 clearly marks the intended use case ('Best for deep research where you want pre-digested synthesis rather than raw pages'), which differentiates it from the raw-fetch siblings. However, it does not explicitly name alternatives such as search_and_fetch or state conditions when one should prefer them.

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