list_agents
List agents the caller can run: their org's agents plus the public h/ ones.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| size | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Computer-Use Agents API
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
B3/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. However, it does not disclose pagination behavior, rate limits, required permissions, or any side effects. It only states 'List agents' without further behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that communicates the core purpose. It is front-loaded and avoids unnecessary words. However, it could include parameter info without losing conciseness.
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?
Given no annotations, low parameter coverage, and sibling tools like 'run_agent', the description is incomplete. It does not explain what the output contains, pagination, or how to interpret results. The output schema exists but does not fully compensate for missing behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two parameters (page, size) with defaults, but the description does not explain their meaning or usage. Schema description coverage is 0%, and the description fails to compensate, providing no parameter semantics.
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 tool lists agents the caller can run, specifying the scope as their org's agents and public 'h/' ones. It uses a specific verb ('list') and resource ('agents'), distinguishing it from sibling tools like 'run_agent' or 'cancel_session'.
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?
The description implies usage for listing available agents before running them, but does not explicitly state when to use this tool versus alternatives like 'run_agent'. No guidance on prerequisites or when not to use it.
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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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A3.6/5.0
Disambiguation5/5
Each tool targets a distinct resource and action: session lifecycle (run, cancel, wait, message, share), file operations (list, read, write), and agent discovery. No two tools have overlapping purposes; even the session-related tools are clearly separated by their verb.
Naming Consistency5/5
All tool names follow a consistent verb_noun snake_case pattern (cancel_session, list_files, run_agent, etc.). The pattern is uniform across session, file, and agent operations, making the API highly predictable.
Tool Count5/5
With 9 tools, the server is well-scoped for a computer-use agent API. It covers agent discovery, session lifecycle, messaging, sharing, and file access without unnecessary bloat, fitting comfortably in the ideal 3-15 range.
Completeness4/5
The tool set covers the core workflow: list agents, run them, wait for results, send follow-ups, cancel, share, and access files. Minor gaps exist (e.g., no list_sessions or delete_file), but they do not block the primary use case.