create_prediction

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

No annotations are provided, so the description must fully disclose behavior. It only states that a chatflow is run and a response is returned, with no details on side effects, authentication requirements, rate limits, or output format. This is insufficient for the agent to anticipate consequences beyond the obvious request-response.

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 two short sentences, front-loaded with the core action and object. No unnecessary words or repetition, making it an efficient and lean description.

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 tool has four parameters including a nested overrideConfig and no output schema, yet the description offers no information about return structure, error behavior, or side effects. It also fails to contextualize how this base version relates to the three specialized prediction tools. Given the complexity and lack of annotations, the description leaves significant gaps.

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 provides detailed descriptions for all four parameters, achieving 100% coverage. The description adds no additional semantic information about parameter usage or relationships. Baseline of 3 is appropriate as the schema does the heavy lifting.

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 runs a Flowise chatflow with a question and returns a response, using a specific verb and resource. It distinguishes this as the generic chatflow interaction tool, but doesn't explicitly differentiate from specialized siblings like create_prediction_with_history or create_prediction_with_files.

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 says 'Use this to interact with AI workflows configured in Flowise,' providing general context for when to use the tool. It lacks any guidance on when to choose this over the sibling variants (with_history, with_files, with_lead) or when not to use it, leaving usage implied rather than explicitly delineated.

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