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Change an autopilot

update_autopilot
DestructiveIdempotent

Change models, intervals, language, the timing gate or AI position control. Changing the timeframe or switching AI control off closes the paper position first.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "autopilot_id": "<autopilot_id>"
    },
    "name": "update_autopilot"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelsNoOnly when the user asks for specific models: agent -> model id from list_models (paid plans). Leave out to run on the user's saved setup (get_settings)
languageNoLanguage of the write-ups, e.g. en, zh-CN, ja (default: the account's)
intervalsNoagent -> seconds between runs (30 s up to a day; fundamental at least 1800); clamped into range
timeframeNoCandle timeframe. Crypto: 1m 5m 15m 1H 4H 1D. Stock: 1H 1D 1W 1mo. Default: the user's saved timeframe (get_settings)
timing_gateNoCrypto: while flat, the timing-gate model (SX-1) scores each candle first and skips the indicator and decision on low-scoring ones (no model call, 0.05 points per skipped candle; the event says skipped: timing_gate)
autopilot_idYesAutopilot id
ai_position_controlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / models / description
      Previous value: -"Per-agent model override, agent -> model id from list_models (paid plans)"New value: +"Only when the user asks for specific models: agent -> model id from list_models (paid plans). Leave out to run on the user's saved setup (get_settings)"
    • removedInput schema / properties / tier
      Removed value: -{
      -  "description": "Model tier (default fast)",
      -  "enum": [
      -    "fast",
      -    "standard",
      -    "frontier"
      -  ],
      -  "type": "string"
      -}
    • changedInput schema / properties / timeframe / description
      Previous value: -"Candle timeframe. Crypto: 1m 5m 15m 1H 4H 1D. Stock: 1m 15m 1H 1D 1W 1mo. Default 15m"New value: +"Candle timeframe. Crypto: 1m 5m 15m 1H 4H 1D. Stock: 1H 1D 1W 1mo. Default: the user's saved timeframe (get_settings)"
  2. Changed2 schema fields changed
    • addedInput schema / properties / intervals / description
      Added value: +"agent -> seconds between runs (30 s up to a day; fundamental at least 1800); clamped into range"
    • addedInput schema / properties / timing_gate / description
      Added value: +"Crypto: while flat, the timing-gate model (SX-1) scores each candle first and skips the indicator and decision on low-scoring ones (no model call, 0.05 points per skipped candle; the event says skipped: timing_gate)"
  3. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already flag this as destructive, idempotent and open-world, but the description adds a concrete, non-obvious consequence: changing the timeframe or disabling AI control closes the paper position first. That is genuine behavioral context beyond the structured fields. It stops short of covering immediacy of effect or what a partial update does to untouched settings.

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?

Two sentences: the first front-loads the mutable surface, the second delivers the one high-value side effect. There is no filler or repetition of the title.

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 7-parameter destructive mutation with nested objects and no output schema, the description covers the most dangerous side effect but leaves open whether changes apply immediately, whether the autopilot must be stopped first, and what happens to omitted fields. Adequate but with clear gaps for a tool of this complexity.

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 description coverage is 86%, so parameters like models, intervals, timeframe and timing_gate are already well documented in the schema. The description's field list echoes those names but adds no syntax, defaults or constraints beyond what the schema states, which is the expected baseline when the schema does the heavy lifting.

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 uses a specific verb ('Change') plus an explicit enumeration of the mutable fields (models, intervals, language, timing gate, AI position control), so an agent knows exactly what this tool does. It doesn't explicitly contrast itself with nearby tools like update_settings or create_autopilot, but the resource (autopilot) is unambiguous from the name and field list.

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?

Usage is only implied: the field list tells the agent this is the tool for modifying an existing autopilot, and the closing sentence warns about a consequence. There is no explicit 'use this instead of X when...' guidance versus update_settings or autopilot_action, and no stated precondition (e.g. whether the autopilot must be stopped).

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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