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tableski

by io.github.yarenty
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market_snapshot

Latest closed 1-hour bar for each tracked market symbol (crypto and PAXG as a gold proxy): close, change over the last bar, 24 hours and 7 days, RSI(14), 50/200-bar moving averages, drawdown from the high of the stored history. Use list_tables for the full bars_* and indicators_* tables. Market data for information only, not financial advice. Source: Kraken public OHLC, bars in UTC, only closed bars.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "market_snapshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolsNoSymbols to include, e.g. ["BTC","PAXG"]; default all (see the symbols table)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and delivers strong context: source (Kraken public OHLC), timezone (UTC), closed bars only, and the precise metrics included. It does not explicitly state read-only status or rate limits, but these are strongly implied by 'public OHLC' and 'snapshot'.

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 front-loaded with the core purpose, followed by routing advice, disclaimer, and provenance. Every sentence earns its place, and the total length is appropriate for the information conveyed.

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

Completeness5/5

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

Given no output schema, the description effectively serves as a return-value specification by listing all metrics included. It also supplies data provenance, timezone, and bar-closure rules, leaving no critical gap for an agent to call the tool correctly.

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 100%, so the single optional 'symbols' parameter is fully documented in the schema. The tool description adds only the example symbols and default-all behavior, which the schema already covers; baseline 3 is appropriate.

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

Purpose5/5

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

The description states a specific verb and resource: 'Latest closed 1-hour bar for each tracked market symbol' and enumerates the exact metrics returned (close, changes, RSI, MAs, drawdown). It clearly distinguishes from list_tables by directing full-table access there.

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 explicitly names an alternative for full tables ('Use list_tables for the full bars_* and indicators_* tables'), implying this tool is for a quick latest snapshot. However, it does not address when to use query_sql or indicators instead, leaving some sibling differentiation 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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