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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 motor 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

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds genuine behavioral context: it is an orientation tool, it returns step-by-step instructions, and its side-effect-free availability signals that the engine is not yet installed. No contradictions 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the call-to-action and ordered from purpose to triggers, which is efficient. The full Portuguese/English duplication and parenthetical tool lists make it longer than strictly necessary, costing a point on tightness.

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?

With no output schema and no parameters, the description carries the full burden and mostly discharges it: it says what it returns (exact steps) and when it fires. It does not spell out the relationship to algomaker_instalar/algomaker_licenca, which would make the onboarding flow fully navigable.

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?

Zero parameters with 100% schema coverage, so there is nothing to document; baseline 4 applies. The description correctly implies no inputs are needed for this call.

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+resource: it explains what AlgoMaker is and returns exact onboarding steps from 'only Claude' to 'mining in my account'. However, it does not clearly differentiate itself from its actual siblings (algomaker_instalar, algomaker_licenca, abrir_conta) — it names non-sibling runtime tools instead, leaving the boundary with the installer/license tools implicit.

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?

'COMECE POR AQUI' plus explicit triggers: use when asked what AlgoMaker is, how to start, how to install, or when the real tools (mine_strategies, portfolio_estrutura, exec_status) are unavailable because the engine is not installed. This gives a clear positive condition and a concrete diagnostic negative condition.

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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