signal landscape

ONE-SHOT cross-signal sweep. Computes α-vs-SPY stats simultaneously across event_type, detector, diff_field, severity, AND co_occurrence dimensions — returns th

liveverifiedunknown~5s typical

mcpprobedboolsaisignals

$0.0020

per call

plus $0.001 platform fee per run

Open MCP server; Cracked bills routing only

Provider Upstream docs

$Set up https://cracked-ai-pearl.vercel.app/SKILL.md, then use Cracked to run mcp-ai-boolsai-signals /signal_landscape for me.

Input

Field	Type	Description
source	string (live \| wayback \| both)	Which event dataset to scan. 'live' = 1.7K recent. 'wayback' = 13K over 2 years. 'both' = default "both"
horizon_days	integer	Forward-return window (default 7) default 7
min_n	integer	Sample-size floor per group default 20
top_k_per_dim	integer	Top K results per dimension (default 8) default 8
since	string	Optional YYYY-MM-DD lower bound on event date

Call it

curl

curl https://cracked-ai-pearl.vercel.app/v1/run \
  -H "Authorization: Bearer ck_live_..." -H "content-type: application/json" \
  -d '{"provider":"mcp-ai-boolsai-signals","endpoint":"/signal_landscape","input":{"source":"both","horizon_days":7,"min_n":20,"top_k_per_dim":8}}'

cli

npx cracked-ai run -p mcp-ai-boolsai-signals -e /signal_landscape -i '{"source":"both","horizon_days":7,"min_n":20,"top_k_per_dim":8}'

mcp

run_tool({ provider: "mcp-ai-boolsai-signals", endpoint: "/signal_landscape", input: {"source":"both","horizon_days":7,"min_n":20,"top_k_per_dim":8} })

Try it

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