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lj22503

InvestBrain

by lj22503
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

user_create_profile

Create a local investor profile in InvestBrain to save risk tolerance, style, goals, and settings for retention tracking before first use.

Instructions

创建本地用户 profile。

首次使用前必须创建，用于留存/活跃度追踪的锚点。

Args:
    nickname: 用户昵称
    risk_profile: 风险偏好，可选 conservative / moderate / aggressive
    investment_style: 投资风格，可选 value / growth / trend / mixed
    experience_years: 投资经验年限
    goals: 投资目标列表，如 ["长期复利", "跑赢沪深300"]
    settings: 附加设置（JSON 对象），如 {"currency": "CNY", "notify_channel": "feishu"}
    user_id: 用户 ID（默认 local 单用户）

Returns:
    {created: true, profile: {...}}

Input Schema

NameRequiredDescriptionDefault
goalsNo
user_idNolocal
nicknameNo
settingsNo
risk_profileNomoderate
experience_yearsNo
investment_styleNovalue

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It discloses the prerequisite, the retention/activity-tracking role, and the return shape ({created: true, profile: {...}}), which is useful. It omits key behavioral facts: whether calling it twice overwrites an existing profile, errors, or is idempotent, and whether any permission/auth is needed.

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?

Purpose is front-loaded in the first sentence, followed by a prerequisite note, then Args and Returns in a scannable structure. The Args block is slightly verbose but each entry earns its place given the 0% schema coverage.

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?

No output schema, but the description supplies the return shape, and with no annotations it covers the prerequisite, all parameters, and the tracking purpose. The main remaining gap is behavior on a pre-existing profile, which matters for a create tool.

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

Parameters5/5

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

Schema coverage is 0%, so the description must carry all parameter meaning, and it does: it documents all 7 params, supplies the enum values for risk_profile (conservative/moderate/aggressive) and investment_style (value/growth/trend/mixed) that the schema lacks, gives example shapes for goals and settings, and notes the user_id default of local.

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 and resource (创建本地用户 profile) and adds that it is the anchor for retention/activity tracking, which is meaningful scope. It does not explicitly contrast itself with the sibling user_update_profile, so an agent must infer create-vs-update from the name.

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?

"首次使用前必须创建" gives a clear prerequisite/when-to-use trigger. However, it never names the alternative for an existing profile (user_update_profile) nor states what happens if a profile already exists, leaving the create-vs-update decision implicit.

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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