USERDATA

query_market

Executes one SELECT query on market tables to retrieve market data for research and analysis.

Instructions

Runs one SELECT on the market tables.

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": {
      "sql": "<sql>"
    },
    "name": "query_market"
  }
}

Input Schema

Name	Required	Description	Default
`sql`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 8, 2026

TDQS

C2.4/5.0

Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. The phrase 'one SELECT' does imply single-statement, read-only execution, which is the one real behavioral constraint disclosed. Missing are dialect, table allowlist, row limits, timeouts, permission requirements, and what happens if a non-SELECT or multiple statements are submitted — all material for a raw-SQL execution tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single sentence is front-loaded and free of filler, so nothing is wasted. The problem is the opposite of verbosity: the sentence is so terse that it under-specifies the tool rather than efficiently describing it.

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?

An output schema exists, so return values need not be explained. But for a raw-SQL execution tool with zero annotations and zero parameter documentation, the description should address at minimum the dialect, permitted tables, and execution limits. None of that is present, leaving the agent under-informed before issuing arbitrary SQL.

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 0%, so the single 'sql' parameter has no documented meaning in structured data. The description implies it should be a SELECT statement, but provides no syntax guidance, no dialect, no example, and no list of legal table names. With full reliance on the description, this compensation is far from adequate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb 'Runs' plus 'one SELECT on the market tables' conveys that this is a read-only SQL query tool against market data, which is more specific than the name alone. However, 'market tables' is undefined (which tables, which schema), and the description never distinguishes this from the sibling query_account, which is presumably also a SQL query tool. The purpose is inferable but not crisply scoped.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use query_market versus query_account or the pull_* tools that also return market/pricing data. No prerequisites, no table restrictions, and no statement about what to do when a query needs more than one statement or non-SELECT operations. The agent must guess entirely from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.