Skip to main content
Glama

wait

Monitor and retrieve results from multiple AI agent processes running in the background. Specify process IDs and optionally set a timeout to collect outputs when all complete.

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?

Since no annotations are provided, the description carries full responsibility. It discloses compact vs verbose defaults but omits behavior on timeout (error or partial results), failure handling, and side effects. Significant gaps remain.

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 concise sentences front-load the core function and then explain key option. No wasted words.

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?

The description lacks details on return value shape (compact vs verbose), error handling for invalid pids or timeouts, and blocking behavior. With no output schema, completeness is insufficient 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%, so baseline is 3. The description adds value for the 'verbose' parameter (explains effect) but nothing new for 'pids' or 'timeout' beyond schema definitions. Marginal improvement.

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

Purpose5/5

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

The description clearly states the verb 'wait' and the resource 'multiple AI agent processes'. It distinguishes from sibling tools like run, kill_process, and get_result by focusing on waiting for completion and returning results.

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

Usage Guidelines3/5

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

Usage is implied for after launching processes with run, but no explicit when-to-use or when-not-to-use guidance is given. Alternatives like get_result for individual results are not mentioned.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mkXultra/ai-cli-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server