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Backtesting Arena

by io.github.Schoasch
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Get On-Chain Series Historical Values

arena_get_onchain_history

How has this on-chain metric moved over time? Returns the full TIME SERIES of one on-chain metric from the Bitcoin Research Kit — date/value pairs in ascending order, with history back to 2009 for most series. Use it for trend and percentile work; for the single current reading call arena_get_onchain_latest, and to discover valid series_ids call arena_list_onchain_series. Values are as-reported: on-chain metrics can be revised retroactively, so this is not a point-in-time vintage. Range capped by tier — the response carries a range block (requested_days, granted_days, clamped, clamp_reason, tier), so a clamped window announces itself instead of silently looking like the full history. [Free 30d / Pro 365d / Power unlimited]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoDays back from today (clamped by tier).
series_idYesBRK series id, e.g. 'mvrv'.

Schema Changelog

Changes observed during successful MCP inspections.

  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: -[
-  "series_id",
-  "context"
-]New value: +[
+  "series_id"
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that values are as-reported and can be revised retroactively (not point-in-time), and it transparently explains tier-based clamping via the 'range' block. It could add more on response format or error behavior, but the key caveats are covered thoroughly. The lack of annotations is mitigated by this strong prose.

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?

Every sentence earns its place. The description leads with intent, explains the data, routes to alternatives, and flags caveats. It is dense but not bloated, and it front-loads the core function. The structure is a model of clarity without superfluous wording.

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

Completeness4/5

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

For a time-series tool with no output schema, the description covers the essential contextual needs: what is returned, how to use it, alternatives, data revision caveat, and tier clamping behavior. It omits explicit mention of pagination or exact number of data points, but the range block and history depth are explained. Minor gaps but overall complete enough for an agent to call confidently.

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?

Schema coverage is 100% and both parameters are documented. The description adds value by explaining the 'days' parameter's interaction with tier limits (Free 30d / Pro 365d / Power unlimited) and by mentioning the 'range' block that reports clamping. It also gives an example series_id ('mvrv'). This goes beyond the schema's basic descriptions, enriching the semantics.

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 the full time series of one on-chain metric as date/value pairs, with history back to 2009. It distinguishes itself from siblings by explicitly naming arena_get_onchain_latest for single readings and arena_list_onchain_series for discovering series IDs. The verb 'returns' and resource 'time series' are specific and actionable.

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 guidance: 'for the single current reading call arena_get_onchain_latest, and to discover valid series_ids call arena_list_onchain_series.' It also states the intended use case ('trend and percentile work'). This is a textbook example of alternating tool routing with clear conditions.

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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