arena_dip_scenario
ActiveTool of Backtesting Arena
Frame a dip/accumulation thesis WITHOUT a recommendation. Given an asset (BTC/ETH/SOL), a named cycle-state preset and a thesis horizon, returns: (1) a tranche LADDER anchored to STRUCTURAL marks (200-week MA, support clusters) below spot — not calendar-DCA, not a price forecast; (2) the cited historical base rate from the analog engine (what forward returns followed comparable states, with effective-n and small-n warnings); (3) the explicit lump-sum-vs-tranche tradeoff (laddering buys lower timing variance, NOT higher expected value). Requires an invalidation point (mandatory: at what scenario is the thesis wrong). Composes the historical-analog + key-levels tools; descriptive only, never a buy/sell signal. This structural framing is MCP-only; a related (different-method, EV/Kelly) interactive tool is at https://tradingstrategies.work/analyse/dip-decision. [API Pro tier]
Parameters schema
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"preset",
"invalidation",
"context"
],
"properties": {
"asset": {
"enum": [
"BTC",
"ETH",
"SOL"
],
"type": "string",
"default": "BTC",
"description": "Which asset. Support-cluster rungs are BTC-only; ETH/SOL use the 200-week MA as the structural mark."
},
"preset": {
"enum": [
"cycle_bottom_cluster",
"cycle_top_cluster",
"deep_fear",
"euphoria"
],
"type": "string",
"description": "Cycle-state preset for the base rate. One of: cycle_bottom_cluster, cycle_top_cluster, deep_fear, euphoria. ETH/SOL: price-derived presets only."
},
"capital": {
"type": "number",
"description": "Optional total capital — if given, each tranche also returns an absolute amount.",
"exclusiveMinimum": 0
},
"context": {
"type": "string",
"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.\""
},
"horizon_days": {
"type": "integer",
"default": 180,
"description": "Thesis horizon in days for the base-rate forward return. Default 180.",
"exclusiveMinimum": 0
},
"invalidation": {
"type": "string",
"minLength": 1,
"description": "MANDATORY: the scenario under which the thesis is wrong (e.g. \"weekly close below the 200-week MA\"). NOT \"where do I buy\"."
},
"risk_aversion": {
"type": "number",
"default": 1,
"description": "Ladder tilt. 1 = equal tranches; >1 = weight deeper marks more (more patient); <1 = front-load toward now. Clamped [0.5, 3].",
"exclusiveMinimum": 0
}
}
}No endpoints wrapped at confidence ≥ 0.70.
Parent server
Backtesting Arena
https://github.com/Schoasch/skill-backtesting-arena
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