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Change the default models

update_settings
Idempotent

Save the user's default models for one market, when they ask to change them: live = the four live agents, deep = the committee seats (one setting for both markets). Paid plans only. The website shows the same setup.

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": {
      "asset": "<asset>"
    },
    "name": "update_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
deepNo
liveNo
assetYescrypto or stock (US stocks and ETFs)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=true), and the description usefully adds the paid-plan gating and the fact that deep is a single setting shared across both markets. However, it never says whether omitting live or deep leaves the other group untouched or wipes it, which is the key behavioral risk for a settings write.

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?

The action and its settings mapping are front-loaded, and each clause ('paid plans only', website parity) carries information. The sentence is dense but has no obvious filler; the trailing website remark is the only borderline clause.

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 nested-object mutation tool with 33% schema coverage and no output schema, the description covers the plan gate and the meaning of the two setting groups. It leaves the genuinely ambiguous points unresolved: whether asset is ignored for deep, and whether a partial payload overwrites the unmentioned group.

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 only 33%, so the description has to carry weight, and it does explain the live/deep split and that deep applies to both markets. The required 'asset' parameter's role is muddied rather than clarified: it is mandatory, yet deep supposedly ignores market, and the description's 'for one market' phrasing never reconciles that. Partial-update semantics for the two optional groups are also unstated.

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 opens with a concrete verb+resource ('Save the user's default models for one market') and then disambiguates the two settings groups, live = the four live agents and deep = the committee seats. That is specific enough to tell it apart from get_settings and the update_* siblings, though it never names get_settings explicitly as the read counterpart.

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?

It gives an explicit trigger ('when they ask to change them') and a prerequisite ('Paid plans only'), which is real routing guidance. It stops short of stating when-not-to-use or pointing at get_settings for reads, so it is clear context without full exclusion logic.

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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