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wait

Collect results from AI agent processes after they complete. Accepts process IDs, optional timeout, and verbose mode for detailed output.

Instructions

Wait for multiple AI agent processes to complete and return their results. Defaults to compact result items; set verbose to true for full metadata and detailed parsed output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pidsYesList of process IDs to wait for (returned by the run tool).
timeoutNoOptional: Maximum time to wait in seconds. Defaults to 180 (3 minutes).
verboseNoOptional: If true, each result item uses the full result shape including metadata fields and detailed parsed output. Defaults to false.
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions defaults (compact results, 180s timeout) but omits blocking behavior, error handling, return value shape, or timeout consequences.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences convey purpose and key option efficiently. No superfluous words, well front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks output schema, so description should detail return values. It only says 'return their results' without explaining format, success/error indicators, or shape of compact vs verbose results. Missing details for a 3-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing adequate parameter descriptions. The description adds context for the verbose parameter by explaining the difference between compact and full results, but does not substantially enhance understanding of pids or timeout beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool waits for multiple processes and returns results. It specifies 'multiple AI agent processes' which distinguishes it from single-result tools like get_result, though no explicit comparison is made.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like get_result or peek. The description only explains the function, not usage context or exclusions.

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

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