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JinyangWang27

people-context

explain_shared_connections

Read-only

Explain how two people are connected through shared group memberships, showing whether they were classmates, teammates, or shared context with dates.

Instructions

Explain how two people are connected through groups they were both recorded in, and when.

Use for shared-background, introduction, and "how do they know each other" questions. Pass each person as an id (person_a_id, person_b_id) or a name (person_a, person_b).

Each connection is one membership of each person in the same group, cited in full. label is classmates (both student in a class) or teammates (both participant in a team) only when the recorded dates prove a common day (temporal: overlap, with the overlap period); otherwise the connection is shared_context only. temporal is disjoint when the dates exclude a common time and unknown when they cannot tell. Sharing a club, household, or community is not friendship, kinship, or acquaintance; different groups under one organization, and people linked through a third person, share nothing here. direct_relationships are recorded relationships between the two, kept apart from derived results. No result means no shared group was found, not that they do not know each other. Only ordinary groups and memberships are used; truncated and memberships_truncated report a partial answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
person_aNo
person_bNo
person_a_idNo
person_b_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.1

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses label classification rules, temporal semantics (`overlap`, `disjoint`, `unknown`), the distinction between derived results and `direct_relationships`, the meaning of empty results, and truncation flags. This is rich behavioral transparency.

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 long but well organized into purpose, usage, output semantics, and caveats. Nearly every sentence carries necessary information, though it is dense and could be slightly tightened without losing meaning.

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

Completeness5/5

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

For a complex analytical tool, the description covers key nuance: no result means no shared group found rather than no relationship, truncation flags signal partial answers, and labels/temporal states are precisely defined. The presence of an output schema removes the need to describe return fields, making this complete.

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?

With zero schema description coverage, the description explains four of the five parameters by clarifying that people can be passed as IDs (`person_a_id`, `person_b_id`) or names (`person_a`, `person_b`). However, `limit` is not described in prose; its meaning is only implied by its name and default value, so parameter coverage is not complete.

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 states a precise action and resource: explaining how two people are connected through shared group memberships, including timing. It is specific enough that an agent can distinguish it from a generic connection search even without reading sibling schemas.

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?

It gives explicit target use cases: 'shared-background, introduction, and how do they know each other questions.' This is clear when-to-use context. However, it does not name alternatives such as the sibling `find_connection` or state when not to use this tool, so it stops short of a 5.

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