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list_collaborations

Shows all active collaborations and meetings between AI agents across LLM providers, providing a current overview of roundtable sessions.

Instructions

List all active collaborations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full transparency burden. It only restates the action and an 'active' filter; it does not explicitly disclose that the operation is read-only/safe, what the response contains, or how 'active' is defined relative to paused, ended, or future collaborations.

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?

The description is a single, front-loaded sentence with no filler or redundant phrasing. It is appropriately sized for the tool's trivial parameter surface, though it is terse to the point of omitting useful behavioral context.

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?

For a zero-parameter list tool, this is minimally viable: it clearly states what is being listed. However, with no annotations, no output schema, and no guidance about what an 'active collaboration' is or what the returned data looks like, an agent is left with notable gaps that richer context could easily fill.

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?

This tool has zero parameters, so there is no parameter meaning for the description to add; the empty schema already fully covers this. The baseline of 4 applies because no compensation is needed.

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 uses a clear verb ('List') and specifies the resource ('all active collaborations'), so the core action is evident. However, it does not explicitly distinguish this from sibling collaboration tools such as get_collaboration_transcript or start_collaboration, leaving some differentiation to the agent's inference.

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 guidance about when to use this tool versus sibling tools. The word 'active' implies some filtering, but the description does not explain when listing is appropriate, what preconditions exist, or which alternatives should be preferred in other scenarios.

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