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Backtesting Arena

Get Live Volatility Phase Snapshots

arena_get_volatility_phases

Is this pair calm or wild right now? Current ATR-based volatility phase (low/normal/high/expansion) per tracked pair, updated daily at 08:00 UTC. This is a single current state — for the time series behind it use arena_get_volatility_history, and for what the phase implies for strategy choice use arena_get_volatility_recommendations. Filter with pair when you only care about one asset instead of pulling all of them. [Free tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pairNoFilter to a single pair, e.g. "BTCUSDT". Omit for all tracked pairs.
asset_typeNoFilter by asset class. Omit for all.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / context
      Removed value: -{
      -  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
      -  "type": "string"
      -}
    • removedInput schema / required
      Removed value: -[
      -  "context"
      -]
  2. Changed1 schema field changed
    • addedInput schema / properties / pair
      Added value: +{
      +  "description": "Filter to a single pair, e.g. \"BTCUSDT\". Omit for all tracked pairs.",
      +  "type": "string"
      +}
  3. Changed1 schema field changed
    • changedInput schema / properties / asset_type / enum
      Previous value: -[
      -  "crypto"
      -]New value: +[
      +  "crypto",
      +  "tokenized_equity",
      +  "tokenized_etf",
      +  "commodities"
      +]
  4. Changed1 schema field changed
    • changedInput schema / properties / asset_type / enum
      Previous value: -[
      -  "crypto",
      -  "stock",
      -  "etf"
      -]New value: +[
      +  "crypto"
      +]
  5. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It reveals that the data is updated daily at 08:00 UTC, is a current snapshot, and mentions the free tier. It doesn't explicitly state side effects or safety, but for a read-only getter this is adequate. It adds context about the update cadence and the distinction from historical data, which is valuable.

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 two concise sentences plus a tier tag, with the key information front-loaded. The opening question draws attention, the core definition follows, then alternatives and filtering tips are compactly placed. Every sentence earns its place with no redundancy or fluff.

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 simple read-only snapshot tool with two optional filters and no output schema, the description is thorough: it specifies the return content (volatility phase per pair), the update frequency, how it differs from related tools, and how to filter. It even notes the free tier. Nothing essential is missing for a correct invocation.

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 both parameters are well-documented in the input schema. The description's note about using `pair` to filter duplicates what the schema already says ('Filter to a single pair... Omit for all tracked pairs'). No new meaning is added for `asset_type`. Thus the description adds minimal value beyond the schema, meriting the baseline 3.

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 clearly states the tool returns a 'current ATR-based volatility phase (low/normal/high/expansion) per tracked pair' and explicitly differentiates it from sibling tools by noting it is a 'single current state' versus the history and recommendation tools. This makes the purpose unmistakable and distinguishes it from the many get_* siblings.

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?

It provides explicit routing: 'for the time series behind it use arena_get_volatility_history, and for what the phase implies for strategy choice use arena_get_volatility_recommendations.' It also gives practical advice on using the `pair` filter to limit results. This leaves no ambiguity about when to choose this tool over its siblings.

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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TDQS

A3.6/5.0
Disambiguation2/5

Many tools cover overlapping market indicators (e.g., cycle state, pulse, bullmarket ampel, volatility phases) and several share similar get_*_history patterns, which could cause an agent to select the wrong one. However, each tool has detailed descriptions with explicit references to related tools to reduce ambiguity.

Naming Consistency3/5

Tool names generally follow a verb_noun pattern (arena_get_*, arena_list_*, arena_run_*, arena_subscribe_*), but there are inconsistencies such as 'validate_strategy' (no arena_ prefix), 'arena_status' (not a clear verb_noun), and variations like 'arena_run_grid_backtest' vs 'arena_run_backtest'.

Tool Count2/5

With 84 tools, the server is heavily over-scoped for a typical MCP server, likely causing navigation and selection overhead. While the domain (crypto backtesting and analytics) is broad, 84 tools exceed reasonable coherence and impose a high cognitive load.

Completeness4/5

The tool surface covers a wide range of analytics (market indicators, backtesting, validation, alerts, subscriptions, reports) with few obvious dead ends. Minor gaps exist like lack of direct portfolio management or strategy editing, but core workflows are well covered.