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gohluke

Dayze MCP

by gohluke

Explain Fact

explain_fact
Read-only

Find evidence for a claim by retrieving provenance from learned facts, life events, and memories, so agents can cite sources instead of inventing them.

Instructions

Return evidence/provenance for a claim: polaris_learned_facts, life_events / life_event_relationships when present, then memories. Use when the agent must cite why it believes something — do not invent sources. ($0.10; API key required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factNoAlias for query
limitNoMax evidence rows 1–20, default 8
queryYesFact or phrase to explain

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
queryYes
messageNo
evidenceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.28.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses the source lookup order, the API-key requirement, the $0.10 cost, and an important integrity constraint against inventing sources. This adds substantial behavioral context that the annotations alone do not provide.

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 three short sentences: function, usage guidance, and cost/auth. Every sentence earns its place, and the most important information is front-loaded.

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?

Given the output schema exists and annotations cover safety, the description provides everything else an agent needs: the provenance strategy, when to invoke it, and operational constraints like API key and cost. Nothing critical is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema already documents all parameters well. The description reinforces the notion of a 'claim' but does not add significant additional parameter semantics beyond what the schema provides.

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 starts with a specific verb and resource: 'Return evidence/provenance for a claim.' It goes further by naming the exact source types to consult and their precedence, which clearly distinguishes this tool from siblings like get_memories or get_life_graph.

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 an explicit trigger condition ('Use when the agent must cite why it believes something') and a clear negative behavior ('do not invent sources'). However, it does not explicitly name alternative tools or describe when NOT to use this tool beyond that one negative instruction.

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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