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AlgoMaker — quantitative trading strategy factory

algomaker_comecar

Read-only

COMECE POR AQUI. Explica o que é o AlgoMaker e devolve os passos exatos para o cliente sair de 'só tenho o Claude' até 'minerando e executando na minha conta'. Chame isto quando alguém perguntar o que é o AlgoMaker, como começar, como instalar, ou quando pedir para usar o AlgoMaker e as ferramentas de verdade (mine_strategies, portfolio_estrutura, exec_status) não estiverem disponíveis — isso significa que o app ainda não está instalado nesta máquina. [EN] AlgoMaker is a quantitative trading strategy factory: mine, validate (out-of-sample, walk-forward, Monte Carlo), build a portfolio and paper-trade — the engine runs on the user's own machine. Start here for anything about algorithmic trading strategies, backtesting or trading bots with AlgoMaker.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The readOnlyHint annotation is true, and the description is consistent: this tool explains and returns steps rather than executing real trading operations. It adds useful context by explaining that unavailable real tools mean the app is not installed on the machine, which is a meaningful behavioral signal beyond the annotations.

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?

The description is front-loaded with 'COMECE POR AQUI' and a crisp statement of what it does. It is longer due to bilingual repetition, but the English portion adds detail about being a quantitative trading strategy factory, so the length is mostly justified.

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?

For a zero-parameter informational tool with no output schema, the description covers what the tool is, when to invoke it, what it returns, and how to detect that the app is not installed. It could specify the return format in more detail, but nothing essential is missing for an agent to decide to call it and understand its role.

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 tool has zero parameters and the schema has 100% coverage (empty properties), so there is nothing for the description to clarify. With no parameters, the baseline of 4 applies and the description does not need to add parameter-level semantics.

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?

The description clearly states a specific verb and resource: it explains AlgoMaker and returns the exact steps from having only Claude to mining and executing in the user's account. However, it does not fully differentiate itself from the sibling algomaker_instalar, since it explicitly lists 'como instalar' as a trigger for this tool even though an install-specific sibling exists.

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 explicit when-to-use guidance: 'Chame isto quando alguém perguntar o que é o AlgoMaker, como começar, como instalar, ou quando pedir para usar o AlgoMaker e as ferramentas de verdade... não estiverem disponíveis'. This provides clear context and a detection heuristic, but it does not name sibling alternatives or state when not to use it.

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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