arena_get_hash_ribbonsAre miners capitulating? Latest Hash Ribbons indicator (Charles Edwards). Returns 30d and 60d hashrate moving averages — when 30d > 60d after a capitulation, signals miner recovery (bullish). [Free tier]
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / contextRemoved 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"
-}Input schema / requiredRemoved value: -[
- "context"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It states that the tool 'Returns' data, implying a read-only operation. It adds the interpretation logic and notes '[Free tier]', hinting at access level. It does not go into potential rate limits or error conditions, but for a zero-parameter read snapshot, the disclosure is adequate and does not contradict any annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a short bracketed note. It front-loads the user-facing question, then explains the output and its interpretation in a clear, efficient manner. Every word earns its place; there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (no parameters, no output schema), the description sufficiently explains what is returned and how to interpret it. It could be slightly more explicit about the asset (e.g., Bitcoin) and the exact output format, but for a snapshot indicator, this is adequate. It covers the core information needed to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
This tool has zero parameters and the schema is empty, so per the baseline rule for 0 params, a score of 4 is appropriate. There are no parameter semantics to add, and the description already covers what the tool returns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'Latest Hash Ribbons indicator' and specifically '30d and 60d hashrate moving averages'. The verb 'Returns' plus the resource (hash ribbons) makes the purpose unambiguous, and it distinguishes itself from sibling indicator tools like arena_get_fear_greed or arena_get_mayer_multiple by naming a unique indicator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The opening question 'Are miners capitulating?' implies the intended use case: assessing miner capitulation and recovery. It explains the signal interpretation (30d > 60d after capitulation = bullish), which gives clear context for when to apply the tool. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of the explicit when/when-not guidance required for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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'.
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.
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.