research_start

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

With no annotations, the description must carry the behavioral burden. It explains the async workflow (poll and import), mode-specific performance (time and source counts), and that notebook_id creates a new notebook if omitted. It does not mention potential side effects like overwriting, but overall provides solid transparency.

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 structured into an intro, use cases, workflow, and args. Every sentence is purposeful, no waste. It is front-loaded with the core action and entirely self-contained.

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 presence of an output schema, the description does not need to detail return values. It provides a complete picture of the tool's purpose, workflow, and parameter effects. The links to sibling tools via workflow enhance 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 0%, but the description compensates fully by listing each parameter with examples, defaults, and explanations (e.g., 'mode: fast (~30s, ~10 sources) | deep (~5min, ~40 sources, web only)'). This adds significant meaning beyond the schema's type and default information.

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 starts with a clear verb and resource: 'Search web or Google Drive to FIND NEW sources.' It lists specific use cases like 'deep research on X' and 'search web for Z,' and distinguishes itself from siblings by outlining the workflow research_start -> research_status -> research_import.

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 explicitly states when to use the tool ('Use this for: ...') and provides mode/source options. However, it does not mention when not to use it or contrast with alternatives like notebook_query, leaving room for improvement.

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