plan_research_workflow

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

No annotations are provided, so the description carries the behavioral disclosure burden. It explains the output fields (intent_summary, suggested_topic, etc.) and workflow (present plan, get confirmation, then call auto_research_topic). It doesn't mention whether the tool has side effects or modifications, but being a planning tool, it is likely read-only. The description could be more explicit about state changes.

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 well-structured with a clear opening sentence, bullet points for output fields, and example phrases. It is front-loaded with the purpose. While somewhat long, every sentence adds value, so it earns its length. Could be slightly more concise without losing information.

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 covers the tool's inputs, outputs, workflow, and interaction with the user (confirming before calling auto_research_topic). It mentions clarifying questions, next_call, and existing cluster matching. Given the complexity of a planning tool, this is fairly complete. However, it doesn't address error conditions or edge cases like when the intent is too vague to plan.

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?

There is only one parameter 'user_intent' with 0% schema description coverage, but the description compensates by explaining what it means: 'freeform user intent' and giving concrete examples like 'I want to learn about X.' This adds significant meaning beyond the schema's type string.

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: 'Convert a freeform user intent into a structured research plan.' It specifies the verb 'convert' and the resource 'freeform user intent,' and distinguishes it from sibling auto_research_topic by calling it a planning step before that.

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?

It explicitly says to call this BEFORE auto_research_topic when the request is vague, ambitious, or could collide with an existing cluster. It provides example user phrases, giving clear context for when to use. However, it doesn't explicitly state when not to use or mention other alternatives besides auto_research_topic.

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