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gohluke

Dayze MCP

by gohluke

Person Interactions

get_person_interactions
Read-only

Find when you last saw a contact by pulling their interaction timeline: messages, calls, meetings, notes, visits, gifts, and co-tagged events. Pass a person ID or name.

Instructions

Relationship timeline for one CRM person: interactions rows (message/call/meeting/note + extended kinds like visit/gift/stayed_over encoded in summary) plus co-tagged calendar events. Prefer this over dumping people.notes for “when did I last see X?”. Pass person_id or name. ($0.10; API key required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoInclusive YYYY-MM-DD filter
fromNoInclusive YYYY-MM-DD filter
kindNoOptional filter: meeting, visit, gift, stayed_over, met, …
nameNo
limitNoMax rows 1–100, default 40
person_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
countNo
eventsNo
person_idNo
truncatedNo
matched_viaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.28.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover read-only and non-destructive behavior, so the description correctly focuses on more useful behavioral details: 'extended kinds like visit/gift/stayed_over encoded in summary' and inclusion of 'co-tagged calendar events'. These reveal data-modeling quirks beyond what readOnlyHint and destructiveHint communicate.

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?

Three dense sentences: purpose, usage guidance, and invocation essentials. No filler or redundant restatement of the schema. The main purpose is front-loaded and every clause adds information.

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?

For a tool with an output schema and read-only annotations, the description covers the core inputs, the interaction-kinds semantics, the calendar-event inclusion, and the cost/auth caveat. It could slightly improve by stating what happens if neither person_id nor name is supplied, but it is otherwise sufficiently complete for an agent to call it correctly.

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 67%, leaving name and person_id bare. The description compensates by stating 'Pass person_id or name,' which clarifies that these are mutually acceptable identifiers. It also reinforces the kind parameter by listing extended kinds like visit/gift/stayed_over, adding meaning beyond the bare schema examples.

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 opens with a specific product: 'Relationship timeline for one CRM person' and enumerates the exact contents (interactions rows, extended kinds, co-tagged calendar events). It is clearly distinct from siblings like get_person_transactions or get_people. This is a strong, specific verb-resource-scope statement.

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

Usage Guidelines5/5

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

It explicitly says when to prefer this tool: 'Prefer this over dumping people.notes for "when did I last see X?"'. It also tells the agent how to identify the person: 'Pass person_id or name.' This gives a concrete usage directive and names an alternative approach to avoid.

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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