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list_relationships

HISTORY: list the customer accounts, recurring team meetings, and people that the user's own Mainroom agents have sat in meetings with — with session counts, when they last met, and how many commitments / open questions / risks are still open. Needs the user's Mainroom API key (shown on the History page at https://app.mainroom.ai — they paste it once). Follow with get_relationship_history for the detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoOptional name filter (account, team, or person).
api_keyYesThe user's Mainroom API key (mr_...), from the History page in the app.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It mentions the API key requirement but does not disclose whether the operation is read-only, has side effects, or modifies any data. The 'list' verb implies a safe operation, but that is not explicitly stated.

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 longer than necessary but well-structured, front-loaded with 'HISTORY:' and then enumerating the returned data. The trailing note about get_relationship_history is relevant and placed appropriately. Slight redundancy with the schema (e.g., api_key format) is acceptable.

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

Completeness4/5

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

Given there is no output schema, the description gives a reasonable picture of what is returned (session counts, last met, commitments/open questions/risks). It also points to the companion detail tool. It could be more explicit about the exact return shape or ordering, but it is sufficient for a list operation.

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?

Schema coverage is 100% for the two parameters. The description adds useful context beyond the schema by explaining that the api_key is shown on the History page and clarifying the query filter applies to accounts, teams, or people. This enhances the schema's bare field descriptions.

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 customer accounts, recurring team meetings, and people the user's agents have met with, including session counts, last meeting time, and outstanding commitments/questions/risks. It also distinguishes itself from the sibling get_relationship_history by noting that tool provides detail.

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

Usage Guidelines4/5

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

The 'HISTORY:' prefix and the phrase 'Follow with get_relationship_history for the detail' explicitly indicate when to use this tool versus the sibling detail tool. It also notes the requirement for the user's API key, though it could more explicitly state 'use this for an overview'.

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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