analyze_velocity_data

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

The annotations already include destructiveHint=true and readOnlyHint=false, but the description adds no additional behavioral context such as what data might be modified, whether results are stored, or any side effects. The only extra information is the data prerequisite (spliced/unspliced layers), which is more about applicability than behavior. Thus, it contributes minimal value beyond the annotations.

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 and front-loaded, stating the main purpose in the first sentence. It then lists the arguments in a simple format. It avoids unnecessary fluff but could be slightly more structured, e.g., by using a numbered list or table for the args. Overall, it earns a 4 for economy of words.

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?

Despite having an output schema and annotations, the description is incomplete for a tool with this complexity. It only names two parameters, while the params parameter contains a large nested object with a dozen fields. There is no guidance on how to choose between methods (scvelo vs velovi), what the output contains, or what happens if certain layers are missing. A more complete description would help an agent correctly configure and invoke the tool.

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%, so the description must compensate. It provides only terse definitions: 'data_id: Dataset ID' and 'params: Velocity parameters (method, scvelo_mode, etc.)'. While it gives examples of sub-parameters, it does not explain the many nested parameters or how they affect the analysis. The params object is a complex nested model with a dozen properties, and the description adds little meaning beyond what the schema already shows.

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: 'Analyze RNA velocity to understand cellular dynamics.' This includes a specific verb ('analyze'), a specific resource ('RNA velocity'), and biological context. It distinguishes itself from sibling tools like analyze_trajectory_data by focusing specifically on RNA velocity, and it mentions the technical prerequisite of needing 'spliced' and 'unspliced' layers.

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 gives a clear context for when the tool is applicable by specifying the requirement for 'spliced' and 'unspliced' layers, which is a key prerequisite. However, it does not mention alternative tools or explicitly state when not to use this tool, so it does not fully meet the 'explicit alternatives' criterion.

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