summarize_docs

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

There are no annotations, so the description must carry the full transparency burden. It fails to disclose behavioral traits such as whether this is a read-only operation, whether it calls an LLM API (cost/latency implications), or how the model/style parameters affect the output. The mention of model options hints at external AI usage but doesn't explicitly state behavior or side effects.

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 extremely concise, using two sentences and a compact param list. Every element adds value—first sentence states purpose, the list documents available options. No filler or repetition.

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 lack of annotations and low schema coverage, the description is minimally viable but not complete. It defines the tool's action but lacks context on when to deploy it relative to sibling tools, how the query parameter is used, or what the output format looks like despite the output schema being present. It covers the basics but leaves gaps for an agent to infer.

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 must explain parameters, but it only lists possible values for style and model, omitting the meaning or role of the required 'query' parameter. It partially compensates by specifying style options, but the critical 'query' param is left undefined, leaving a significant semantic gap.

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 'Synthesize a final answer from a list of document strings' uses a specific verb (synthesize) and resource (document strings), clearly distinguishing it from sibling tools like research or scrape_url. The purpose is unambiguous and immediately conveys the core function.

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?

Usage is implied by the description: you should use this when you have document strings and need a synthesized answer. However, there is no explicit when-to-use, exclusions, or alternatives mentioned relative to sibling tools such as research or rerank_docs, so the guidance remains implicit rather than instructive.

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