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Backtesting Arena

by io.github.Schoasch

Get Universe Detail

arena_get_universe

Which pairs are in this universe? Returns one pair universe in full: its id, label, selection rule and the complete list of pairs it currently contains. Use it to see what you are about to test BEFORE handing a universe_id to arena_run_universe_backtest, or to resolve a universe into explicit pairs. For the list of available universes call arena_list_universes. Universes reflect the CURRENT membership — they are not point-in-time, so a backtest over them carries survivorship bias for the earlier years. [Free tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
universe_idYesUniverse id, e.g. 'top-10-crypto'.

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"
-}
    • changedInput schema / required
      Previous value: -[
-  "universe_id",
-  "context"
-]New value: +[
+  "universe_id"
+]
  2. 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 burden of behavioral disclosure. It discloses a critical behavioral caveat: 'Universes reflect the CURRENT membership — they are not point-in-time, so a backtest over them carries survivorship bias for the earlier years.' It also states the output contents explicitly. Although it lacks details about error handling or rate limits, the survivorship bias warning is a valuable behavioral insight that goes beyond a simple read operation.

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 concise and well-structured. It starts with a user-facing question to frame the purpose, then states what it returns, provides usage guidance, points to an alternative, and ends with a critical caveat. Every sentence adds value; there is no repetition or filler. The most important information is front-loaded.

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 single-parameter read operation, the description is complete. It explains exactly what the tool returns (id, label, selection rule, pair list), when to use it (before backtests or to resolve universes), and what alternatives exist (list_universes). It also highlights the survivorship bias implication, which is essential context for the backtest use case. No output schema is provided, but the description compensates by listing the return fields.

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%, and the schema already explains the parameter: "Universe id, e.g. 'top-10-crypto'." The description does not add new semantic details about universe_id itself, only hints at its usage in context (handing to a backtest). Since the schema fully documents the parameter, the baseline of 3 is appropriate, with no additional value provided by the description.

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 opens with a direct question ('Which pairs are in this universe?') and then states the exact resource and action: 'Returns one pair universe in full: its id, label, selection rule and the complete list of pairs it currently contains.' It clearly distinguishes from siblings by referencing arena_list_universes for the list and arena_run_universe_backtest for testing. The verb 'returns' and the resource 'pair universe' are specific and unambiguous.

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?

The description explicitly tells the agent when to use this tool: 'Use it to see what you are about to test BEFORE handing a universe_id to arena_run_universe_backtest, or to resolve a universe into explicit pairs.' It also points to the alternative for listing universes: 'For the list of available universes call arena_list_universes.' This provides clear when-to-use and when-to-use-another guidance.

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