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by io.github.Schoasch
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Get Bullmarket Ampel Snapshot

arena_get_bullmarket_ampel

Is this still a bull market? Bitcoin Bullmarket-Ampel current state (0-5 active stages). Returns active_count, a stages[] breakdown (each stage with key, label, active and since = first day of its current state; null when the state predates the 400-day lookup) and stage_history — per day active_count PLUS all five per-stage booleans, so which stage flipped when is readable directly (history_days 1-365, default 30). Higher count = more bull-market signals firing. Stages evaluate weekly 20W/50W-MA conditions. [Free tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
history_daysNoDays of stage_history to return (1-365, default 30). Each row carries active_count plus all five per-stage booleans, so stage flips are readable per day instead of only via the derived `since` of the current run.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / history_days
      Added value: +{
+  "description": "Days of stage_history to return (1-365, default 30). Each row carries active_count plus all five per-stage booleans, so stage flips are readable per day instead of only via the derived `since` of the current run.",
+  "maximum": 365,
+  "minimum": 1,
+  "type": "integer"
+}
  2. 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"
-]
  3. First observed

TDQS

A4/5.0
Behavior4/5

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

No annotations exist, so the description carries the burden, and it discloses substantial behavior: output shape (active_count, stages[], stage_history), the null `since` edge case for pre-400-day states, per-day booleans, weekly 20W/50W-MA evaluation, and free-tier status. It doesn't explicitly address rate limits or side effects, but the read-only nature is strongly implied by 'Returns'.

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 dense but mostly front-loaded: it leads with the purpose, then return structure, parameter behavior, interpretation, and cadence. A few long parentheticals make it parse slightly harder, but no sentence is wasted.

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?

With no output schema, the description must explain return values, and it does: active_count, stages[] fields including the null `since` semantics, and stage_history as per-day booleans. The parameter bounds, default, evaluation frequency, and free-tier context are also present, so an agent has enough to invoke and interpret the result correctly.

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 coverage is 100%, and the schema's parameter description already contains the same detail about history_days bounds, default, and per-day booleans. The tool description repeats that content without adding new meaning, so the baseline 3 applies.

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 the exact question it answers and names a specific resource: the Bitcoin Bullmarket-Ampel. It clearly defines scope (current state 0-5 plus history) and the unique 'stages' concept, distinguishing it from generic market/correlation siblings without ambiguity.

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 rhetorical 'Is this still a bull market?' and 'Higher count = more bull-market signals firing' imply the use case: assessing bull-market strength via the Ampel stages. However, it does not state when to prefer this over related siblings (e.g., cycle, market structure, macro regime), leaving the selection logic implicit.

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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