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load_memory_persona

Load a consented public or imported memory profile as context for a clearly labeled AI simulation, so the host AI converses from that archive without claiming to be the person.

Instructions

Load a consented public/imported memory profile as context for a clearly-labeled AI simulation. The host AI should then converse using only this archive, never claiming to literally be the person.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
profileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose meaningful constraints: the profile must be consented, the simulation must be clearly labeled, and the AI must not claim to literally be the person. It omits operational behavior like error handling for unknown profiles, what limit/query actually do, or what is returned.

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?

Two sentences, tightly front-loaded with the action and then the behavioral constraint. No filler, and the ethical directive is not buried.

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

Completeness2/5

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

No output schema and no annotations mean the description must do all the work, yet three parameters are undocumented and the return shape is unspecified. It is strong on ethics but inadequate for correct invocation of a parameterized retrieval tool.

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

Parameters2/5

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

Schema description coverage is 0% for three parameters (profile, query, limit), and the description explains none of them. 'This archive' faintly gestures at the profile argument, but there is no indication of query's filtering role or limit's cap on returned items, leaving the required parameter and the retrieval controls undocumented.

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?

States a specific verb (load) and resource (a consented public/imported memory profile) used as context for an AI simulation, which is distinct from siblings such as create_memory_profile or import_public_memory. It is clear what the tool does, though it never explicitly names or contrasts itself against a sibling.

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

Usage Guidelines3/5

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

The phrase 'as context for a clearly-labeled AI simulation' implies the use case (persona simulation over an archive), and 'converse using only this archive' hints at intended downstream behavior. However, it gives no explicit when-to-use versus list_memory_profiles or search_memory, and no prerequisites such as the profile needing to already exist or be consented/imported.

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