deep_research

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

No annotations are provided, so the description bears full responsibility. It discloses the pipeline, model used (DeepSeek-V4), tunables with defaults, requirements (DEEPSEEK_API_KEY), and that search/fetch are keyless. It does not mention failure modes or rate limits, but the cost/speed tradeoff is noted.

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 concise (about 80 words) and well-structured: purpose sentence, pipeline overview, parameter explanation, and requirements. No wasted words; each sentence adds distinct value.

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, 0% schema coverage, and existence of an output schema, the description fully covers what the tool does, how it works, its parameters, prerequisites, and output format. No critical information is missing.

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 input schema has 0% description coverage, but the description explains each parameter's meaning and default behavior: breadth (sub-queries per round), depth (rounds), max_sources (pages read). The query parameter is self-explanatory. This fully compensates for the schema 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 clearly states the tool's purpose: 'Run a multi-step deep-research investigation and return a cited report.' It specifies the verb (run investigation), resource (deep research), and output (cited report). It distinguishes itself from sibling tools like web_search by implying a multi-step, citation-generating process.

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 this tool (when a thorough, cited investigation is needed) vs simpler tools like web_search. However, it does not explicitly state when not to use it or list alternatives, though the pipeline details make the differentiation clear.

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