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万忆导入档案

Update user preference profiles—trading style, risk appetite, writing style, personal info—and save them to pinned memory for consistent, personalized AI behavior.

Instructions

更新用户偏好档案(交易风格/风险偏好/写作风格/个人信息等),同时存入道级钉住记忆

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes用户档案数据(任意键值对)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose a meaningful side effect: '同时存入道级钉住记忆' (also stored into Dao-level pinned memory). However, it does not clarify merge versus replace behavior, reversibility, or any access constraints.

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?

One compact sentence front-loads the main action, groups examples in parentheses, and appends the side effect. No redundant or filler content.

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

Completeness3/5

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

For a single-parameter tool with 100% schema coverage, the description is mostly adequate but leaves gaps: no explanation of whether the data merges with existing profile fields, what '道级钉住记忆' fully implies, or what result the agent should expect given there is no output schema.

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?

The schema already fully describes the sole parameter 'data' as '用户档案数据(任意键值对)'. The description adds practical value by enumerating likely key categories such as trading style, risk preference, writing style, and personal info, helping an agent populate the arbitrary object.

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?

States a specific verb and resource: '更新用户偏好档案' (update user preference profile), with concrete examples of covered fields. The target resource is distinct from all sibling memory tools such as 万忆错题本, 万忆经验库, and 万忆召回记忆.

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 parenthetical examples ('交易风格/风险偏好/写作风格/个人信息等') imply when to use the tool, but there is no explicit guidance about when not to use it or which sibling tool to choose instead. Usage is inferred rather than stated.

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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