Run a prediction on a Replicate deployment

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

The description fully discloses that the tool is a blocking write operation (non-readonly), auto-downloads by default, supports optional timeout, and returns a standard prediction result with inline previews, URLs, local paths, and prediction ID. This adds value beyond the annotations (readOnlyHint=false) and schema by detailing the synchronous execution behavior and return format.

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 well-structured: a clear opening sentence followed by a bulleted Args block. Every sentence is informative with no redundancy. The structure aids quick scanning for the agent.

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 has 4 parameters, no output schema, and moderate complexity, the description covers all essential aspects: the action, blocking behavior, download behavior, timeout handling, and return value components. It also mentions URL expiration for download=false, which is not in the schema. The description is fully adequate for agent understanding.

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 coverage is 100%, and the description essentially restates the schema parameter descriptions (e.g., deployment as 'owner/name', input as JSON object, download boolean, timeout optional with max wait). The description does not add significant new meaning beyond clarifying that the input shape matches the underlying model's expectations. Baseline score of 3 is appropriate.

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 prediction against a deployment's current release, and distinguishes it from siblings like replicate_run_model by noting the deployment context and the auto-download behavior. The verb 'run' and resource 'deployment' are specific and unambiguous.

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 explains that the tool blocks until completion and auto-downloads outputs, mirroring the curated generate_* tools. It also notes that a timeout parameter can return a pending result for polling via replicate_get_prediction. However, it does not explicitly state when to use this tool versus alternatives like replicate_run_model, which may be confusing in some contexts.

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