hpsilab-mcp

Register a Free Account

register_account

Call this when you are hitting anonymous daily limits and want a higher
allowance. You do not need a password, a wallet, or a web browser. The
account is bound to you server-side, so calls you make after this are
metered as your account even though you cannot change your own
Authorization header.

Registering keeps the anonymous daily allowance until the email address is
confirmed; confirming it unlocks the full Free plan. Ask the human you are
working with to click the link in the email that will arrive.

A valid user email address is required. Do not call this tool with an
empty or fabricated email address. If the user's email is unavailable,
ask the user to provide it before calling register_account.

Args:
    email: The real user email address that will receive verification.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`email`	Yes

TDQS

A5/5.0

Behavior5/5

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

The description goes beyond the annotations by explaining the server-side binding, metering behavior, and the email confirmation workflow: 'The account is bound to you server-side...', 'Registering keeps the anonymous daily allowance until the email address is confirmed; confirming it unlocks the full Free plan.' It also discloses the human involvement needed for verification. No contradiction with annotations.

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 well-structured into four focused paragraphs, each delivering specific information: outcome, usage trigger, confirmation flow, and email requirement. The main purpose is front-loaded, and every sentence adds value, making it both concise and complete.

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?

For a tool with no output schema and a single parameter, the description is fully sufficient. It covers the trigger, prerequisites, immediate result (API key), long-term behavior (plan upgrade), and human verification step. It even addresses edge cases like missing email. This is complete for an agent to safely invoke the 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?

The schema only provides the format 'email', but the description's 'Args' section adds real meaning: 'email: The real user email address that will receive verification.' It also warns against empty or fabricated addresses, clarifying the quality and purpose of the parameter.

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 direct statement: 'Register a free hpsilab account for yourself, with no human involvement, and receive an API key immediately.' This clearly identifies the action, resource, and outcome. It also distinguishes the tool from its stock-analysis siblings by focusing on account registration.

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?

Explicit guidance is provided: 'Call this when you are hitting anonymous daily limits and want a higher allowance.' It also includes a negative rule: 'Do not call this tool with an empty or fabricated email address. If the user's email is unavailable, ask the user to provide it before calling register_account.' This covers both when to use and when not to.

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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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct purpose: individual quant analyses (AI prediction, IV, Monte Carlo, option pressure, equity curve, risk scan), aggregation (analyze_stock), output generation (images, report), and account registration. No two tools are likely to be confused.

Naming Consistency5/5

All tool names follow a uniform verb_noun snake_case pattern (e.g., get_ai_prediction, generate_stock_images, register_account). The convention is applied consistently across the entire set.

Tool Count5/5

10 tools is well within the ideal 3-15 range and covers the full stock-analysis workflow: data gathering, analysis, aggregation, and report generation. Each tool contributes distinct functionality without bloat.

Completeness5/5

The tool set comprehensively covers the domain of quant stock analysis: predictive models, backtesting, options/IV analysis, risk scanning, aggregated analysis, and visual/report outputs. No obvious dead ends or missing core operations for the intended purpose.

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