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Backtesting Arena

by io.github.Schoasch

Get BTC Key Levels (S/R clusters + indicator levels)

arena_get_key_levels

Which price levels matter above and below spot? Reproducible Bitcoin structural levels on BOTH sides of spot, in TWO distinct provenance classes. (1) resistance/support: swing-pivot clusters — where past pivot highs+lows cluster into price zones (touch-count, band, last-touch date, signed distance), resistance above spot, support below, nearest-first. (2) indicator_levels.above / .below: named indicator STANDS as marks — 200-day & 200-week simple moving averages, short-term-holder cost basis, Pi-Cycle legs — each carrying its source, formula and as_of date. The two classes are kept separate on purpose: pivots are where price REACTED before, indicator levels are where an indicator STANDS now. Both are measured price clusters: they say where trading has concentrated, not where anyone defends a level. [Free tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed2 schema fields changed
    • 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. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full behavioral burden. It adds meaningful context: levels are 'reproducible', 'measured price clusters' not 'defended levels', and notes a free tier. It discloses that the two classes are kept separate on purpose. This goes beyond a generic 'get levels' description, though it does not mention rate limits or response format.

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 description is somewhat long but well-structured with a front-loaded question and clear numbered classes. Every sentence adds distinct information (provenance, purpose, free tier). No redundancy, but slightly verbose for a zero-parameter tool.

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 zero-parameter, no-output-schema tool, the description is complete. It explains what levels are included, how they are derived, the separation of classes, and the free tier limitation. Nothing essential is missing for an agent to invoke the tool correctly.

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

Parameters4/5

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

The input schema has zero parameters, so the baseline is 4. The description correctly focuses on the output content rather than parameter details, which is appropriate. No further parameter clarification is needed.

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 ('Get') and resource ('BTC Key Levels') and immediately clarifies it returns structural levels in two provenance classes (pivot clusters and indicator levels). It clearly distinguishes this from the many sibling tools by enumerating what is included, without needing to compare to others.

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

Usage Guidelines3/5

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

The description implies usage: it answers 'Which price levels matter above and below spot?' and explains the two classes. However, it does not explicitly name alternative tools or state when not to use this tool. Given the large sibling list, more explicit routing (e.g., 'for indicator-only values use arena_get_indicator_snapshot') would improve clarity, but the context is understandable.

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.

Resources