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Multi-Timeframe Analysis

multi_timeframe_analysis
Read-only

Multi-timeframe alignment analysis (Weekly → Daily → 4H → 1H → 15m).

Canonical name is exactly `multi_timeframe_analysis` (there is no
"get_multi_timeframe_analysis" tool). Use this for cross-timeframe trend
alignment on ONE symbol; for a single-timeframe deep dive use
`coin_analysis`; for TA + sentiment + news use `combined_analysis`.

Example: multi_timeframe_analysis(symbol="SOLUSDT", exchange="BINANCE")

Args:
    symbol: Bare ticker, no exchange prefix — crypto: "BTCUSDT"; stocks: "COMI" (EGX), "THYAO" (BIST), "600519" (SSE), "300251" (SZSE), "2330" (TWSE), "3105" (TPEX), "GDX" (AMEX)
    exchange: Exchange — crypto: KUCOIN, BINANCE, MEXC; stocks: EGX, BIST, NASDAQ, NYSE, AMEX, NYSEARCA, PCX, SSE, SZSE, TWSE, TPEX, EPA (Euronext Paris), AMS, BRU, LIS, MIL, LSE, SIX, BME, XETRA, FWB, TSX, TSXV, NSE, BSE (India), IDX (Indonesia)

Input Schema

NameRequiredDescriptionDefault
symbolYes
exchangeNoKUCOIN

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds useful behavioral context: the exact timeframes analyzed and that the operation is scoped to a single symbol. It does not describe output format or latency, but with annotations carrying the safety profile this is solid.

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?

Purpose and usage are front-loaded, followed by the canonical-name guard and an example. The Args section duplicates schema content somewhat, but every part (timeframes, routing, param formats) earns its place and the message stays readable.

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?

For a 2-parameter read-only analysis tool with no output schema and no nested objects, the description covers purpose, alternatives, parameter formats, and an invocation example. Nothing an agent needs in order to call it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must carry the full burden and does: it documents the symbol format (bare ticker, no exchange prefix) with concrete crypto and multi-market stock examples, and enumerates the accepted exchange values, none of which appear in the schema. This fully compensates for the coverage gap.

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?

Opens with a specific verb+resource and scope: 'Multi-timeframe alignment analysis (Weekly → Daily → 4H → 1H → 15m)' and 'cross-timeframe trend alignment on ONE symbol'. It explicitly names the sibling tools it is not (coin_analysis, combined_analysis), so an agent can route without opening schemas.

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

Usage Guidelines5/5

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

Provides explicit when-to-use rules and named alternatives: single-timeframe deep dive → coin_analysis, TA + sentiment + news → combined_analysis. The 'ONE symbol' constraint further clarifies fit, leaving nothing to inference.

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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