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Act on the paper position

autopilot_action
Destructive

Change the autopilot's paper position by hand, always at the server's price: open, add, reduce, close, set_levels, place_order, replace_order, cancel_order, set_timeframe. Stocks are long only, and intraday stock entries need the market open.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideNo
priceNoplace_order / replace_order: resting price
actionYes
fractionNoreduce: share of the position
quantityNoCoins or shares
stop_lossNo
timeframeNoset_timeframe: the new timeframe (closes the position first)
expires_inNoOrder lifetime in seconds
order_typeNo
take_profitNo
autopilot_idYesAutopilot id
notional_usdNoSize in USD instead of quantity

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false, so the danger profile is covered. The description adds genuine value beyond that: execution always happens at the server's price, stocks are long-only, and intraday entries require the market to be open. It still doesn't say what a close/reduce destroys or whether changes are reversible.

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?

Two sentences with no filler: the core purpose is front-loaded, followed by the operating constraints. The action enumeration is long and largely redundant with the enum, which costs a point, but nothing is padded.

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

Completeness3/5

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

For a 12-parameter, multi-action destructive mutation with no output schema, the description gives constraints but omits which parameters apply to which action, permissions/auth requirements, and what a call returns (e.g., resulting position or order id). The per-action param hints live in the schema, but the description alone is only partially complete.

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

Parameters3/5

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

Schema coverage is a middling 58%, with several parameters (stop_loss, take_profit, order_type, side, quantity) undocumented. The description re-lists the action enum values, which duplicates the schema rather than adding meaning, and only 'always at the server's price' adds anything beyond the structured fields. It does not compensate for the coverage gap.

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 and resource ('Change the autopilot's paper position by hand') and enumerates the nine actions, which is enough to distinguish it from config-oriented siblings like update_autopilot or start/stop_autopilot. It never names a sibling explicitly, so it stops short of the top band.

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?

It supplies real usage constraints ('Stocks are long only', 'intraday stock entries need the market open') and implies this is a manual override ('by hand'). However, it never says when to prefer this over update_autopilot or the automated autopilot flow, so the when-to-use vs alternatives is left implicit.

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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