Individual skill
edge-candidate-agent
Generate and prioritize US equity long-side edge research tickets from EOD observations, then export pipeline-ready candidate specs for trade-strategy-pipeline Phase I. Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into `strategy.yaml` + `metadata.json`, or preflight-check interface compatibility (`edge-finder-candidate/v1`) before running pipeline backtests.
skills/edge-candidate-agent/SKILL.md
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SKILL.mdcore · 5,813 bytesSKILL.mdcore · 5,813 bytesSKILL.mdcore · 5,813 bytesSKILL.mdcore · 5,813 bytesSKILL.mdcore · 5,813 bytesagents/openai.yamlasset · 282 bytesreferences/ideation_loop.mddoc · 1,281 bytesreferences/pipeline_if_v1.mddoc · 1,589 bytesreferences/research_ticket_schema.mddoc · 1,274 bytesreferences/signal_mapping.mddoc · 1,208 bytesrequirements.txtdoc · 238 bytesscripts/auto_detect_candidates.pyruns · 69,920 bytesscripts/candidate_contract.pyruns · 7,974 bytesscripts/export_candidate.pyruns · 11,750 bytesscripts/tests/conftest.pyruns · 148 bytesscripts/tests/synthetic_ohlcv.pyruns · 4,394 bytesscripts/tests/test_auto_detect_candidates.pyruns · 8,593 bytesscripts/tests/test_auto_detect_dataframes.pyruns · 25,392 bytesscripts/tests/test_auto_detect_main.pyruns · 16,674 bytesscripts/tests/test_auto_detect_units.pyruns · 13,857 bytesscripts/tests/test_candidate_contract.pyruns · 7,203 bytesscripts/tests/test_contract_export_validate_edges.pyruns · 14,693 bytesscripts/tests/test_export_candidate.pyruns · 7,698 bytesscripts/tests/test_validate_candidate.pyruns · 7,589 bytesscripts/validate_candidate.pyruns · 5,068 bytes
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# Edge Candidate Agent
## Overview
Convert daily market observations into reproducible research tickets and Phase I-compatible candidate specs.
Prioritize signal quality and interface compatibility over aggressive strategy proliferation.
This skill can run end-to-end standalone, but in the split workflow it primarily serves the final export/validation stage.
## When to Use
- Convert market observations, anomalies, or hypotheses into structured research tickets.
- Run daily auto-detection to discover new edge candidates from EOD OHLCV and optional hints.
- Export validated tickets as `strategy.yaml` + `metadata.json` for `trade-strategy-pipeline` Phase I.
- Run preflight compatibility checks for `edge-finder-candidate/v1` before pipeline execution.