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alpha-forge-mcp

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save_strategy

Register a trading strategy by providing its JSON definition. Validates and saves the strategy, enabling subsequent backtesting and optimization.

Instructions

Register a strategy from its JSON body (not a file path; agent-friendly).

Pass the full strategy-definition JSON as a string; it is validated as a JSON object
and written to a temp file before `strategy save`. Returns {output}. A registered
strategy is the prerequisite for run_backtest/run_optimize. Reports progress to
capable clients; has an execution timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
json_bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataYes
errorYes
Behavior4/5

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

Adds behavioral context beyond annotations: internal steps (validated, written to temp file), progress reporting, and execution timeout. No contradiction with annotations; they are consistent with a non-read-only, non-idempotent write operation.

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?

Description is concise with two main sentences plus a brief note. Every sentence adds value: first states action and clarification, second details processing, third adds context on prerequisite, progress, and timeout. No unnecessary information.

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?

Given an output schema exists, the description need not detail returns. It covers validation, file writing, prerequisite for other tools, progress, and timeout. Could be more complete by mentioning error handling or size limits, but adequate for an AI agent.

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?

Schema coverage is 0%, so description must compensate. It explains json_body as a full strategy-definition JSON string, and describes what happens to it (validated, written to file). Does not detail required fields within the JSON, but provides sufficient meaning for an agent to understand 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 clearly states the verb 'Register' and the resource 'a strategy', and distinguishes itself by noting it takes JSON body, not a file path. It also mentions it's a prerequisite for run_backtest/run_optimize, setting it apart from sibling tools.

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?

Provides explicit guidance on when to use (to register a strategy for backtesting) and what to pass (full JSON string). Implicitly tells when not to use (if already registered). Mentions validation and prerequisite, but lacks direct comparison to alternatives.

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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