Agent skill · data analytics · tradermonty
edge-concept-synthesizer
Abstract detector tickets and hints into reusable edge concepts with thesis, invalidation signals, and strategy playbooks before strategy design/export.
Why this skill is useful
Adds a Python script that synthesizes edge concepts from ticket data, providing structured outputs that the AI wouldn't generate on its own.
What it needs
Requires python, pyyaml installed locally. About 1k tokens when loaded. Last updated 2026-08-06. 2,581 stars on the source repository.
What this skill does
Edge Concept Synthesizer Overview Create an abstraction layer between detection and strategy implementation. This skill clusters ticket evidence, summarizes recurring conditions, and outputs edgeconcepts.yaml with explicit thesis and invalidation logic. When to Use You have many raw tickets and need mechanism-level structure. You want to avoid direct ticket-to-strategy overfitting. You need concept-level review before strategy drafting. Prerequisites Python 3.9+ PyYAML Ticket YAML directory from detector output (tickets/exportable, tickets/researchonly) Optional hints.yaml Output edgeconcepts.yaml containing: concept clusters support statistics abstract thesis invalidation signals export readiness flag Workflow 1. Collect ticket YAML files from auto-detection output. 2. Optionally provide hints.yaml for context matching. 3. Run scripts/synthesizeedgeconcepts.py. 4. Deduplicate concepts: merge same-hypothesis concepts with overlapping conditions (containment > threshold). 5. Review concepts and promote only high-support concepts into strategy drafting. Quick Commands Resources skills/edge-concept-synthesizer/scripts/synthesizeedgeconcepts.py references/conceptschema.md
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills tradermonty/edge-concept-synthesizer