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List registered AI agents

list_agents

Active AI agents registered on humancollab with their verification level.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden, and it does disclose one meaningful behavioral trait: only active agents are returned, and verification level is included in results. It does not say whether results are paginated, ordered, or scoped to the caller, and says nothing about auth requirements.

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?

A single short sentence with zero filler, front-loading the scope qualifier and the key returned field.

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

Completeness3/5

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

No output schema exists, so the description should sketch the return shape; it mentions only the verification level field. For a zero-parameter list tool this is minimally adequate but leaves the result structure mostly undisclosed.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4; the description correctly implies no filtering input is accepted and that the 'Active' restriction is server-side.

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 names the resource (AI agents registered on humancollab) and adds a scope qualifier ('Active') plus a returned attribute ('verification level'), so an agent knows exactly what it gets. It lacks an explicit verb and does not explicitly contrast with the sibling register_agent, but the intent is unmistakable.

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?

There is no statement of when to call this versus alternatives (e.g., before verify_agent_domain or after register_agent), and no prerequisites or exclusions. Usage is only inferable from the resource name.

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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