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AlgoChains

AlgoChains MCP Server

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by AlgoChains

run_prop_fund_autopilot

Read-onlyIdempotent

Evaluates trading strategies against eligible prop firm funds by analyzing real data, simulating drawdown, and providing a verified recommendation (GO, HOLD, or NO-GO) without executing trades.

Instructions

End-to-end read-only pipeline: build real-data inputs for a strategy, evaluate vs every eligible fund (or a filtered set), simulate drawdown, and return a prioritized recommendation (GO / HOLD / NO-GO) with rules-verified fields. Never commits fees or launches bots.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoMNQ
fund_keysNoOptional filter, e.g. ['apex_50k_eod','mffu_core_50k']
account_idNo
lookback_daysNo
strategy_nameNoFUTURES_SCALPER_UPGRADED
fills_overrideNo
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds context by stating 'read-only pipeline' and 'Never commits fees or launches bots', reinforcing safety. It also describes the output (recommendation with GO/HOLD/NO-GO). 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 two sentences: first details the pipeline, second clarifies safety. No wasted words, front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite describing high-level flow, the description lacks detail on parameter values, return format (besides recommendation type), and edge cases. With 6 parameters, no output schema, and low schema coverage, more information is needed for an agent to use the tool correctly.

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

Parameters2/5

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

Schema description coverage is only 17% (only fund_keys has a description). The description does not explain any of the 6 parameters (symbol, account_id, lookback_days, strategy_name, fills_override) beyond the general pipeline. For a tool with low coverage, the description should add meaning but fails to do so.

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 the verb 'run' and the resource 'prop_fund_autopilot', detailing an end-to-end pipeline: build inputs, evaluate, simulate drawdown, return recommendation. It explicitly says what it does not do (never commits fees or launches bots). However, it does not differentiate from siblings like 'evaluate_strategy_for_prop_fund' or 'run_backtest'.

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?

The description implies usage for exploration and evaluation by stating it is read-only and never commits fees or launches bots. However, it does not explicitly provide when to use or when not to use, nor does it mention alternatives among siblings.

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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