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` +

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. Prerequisites Python 3.9+ with PyYAML installed. Access to the target trade strategy pipeline repository for schema/stage validation. uv available when running pipeline managed validation via pipeline root . Output strategies/<candidate id /strategy.yaml : Phase I compatible strategy spec. strategies/<candidate id /metadata.json : provenance metadata including interface version and ticket context. Validation status from scripts/validate candidate.py (pass/fail + reasons). Daily detection artifacts: daily report.md market summary.json anomalies.json watchlist.csv tickets/exportable/ .yaml tickets/research only/ .yaml Position in Split Workflow Recommended split workflow: 1. skills/edge hint extractor : observations/news hints.yaml 2. skills/edge concept synthesizer : tickets/hints edge concepts.yaml 3. skills/edge strategy designer : concepts strategy drafts + exportable ticket YAML 4. skills/edge candidate agent (this skill): export + validate for pipeline handoff Workflow 1. Run auto detection from EOD OHLCV: skills/edge candidate agent/scripts/auto detect candidates.py Optional: hints for human ideation input Optional: llm ideas cmd for external LLM ideation loop 2. Load the contract and mapping references: references/pipeline if v1.md references/signal mapping.md references/research ticket schema.md references/ideation loop.md 3. Build or update a research ticket using references/research ticket schema.md . 4. Export candidate artifacts with skills/edge candidate agent/scripts/export candidate.py . 5. Validate interface and Phase I constraints with skills/edge candidate agent/scripts/validate candidate.py . 6. Hand off candidate directory to trade strategy pipeline and run dry run first. Quick Commands Daily auto detection (with optional export/validation): Create a candidate directory from a ticket: Validate interface contract only: Validate both interface contract and pipeline schema/stage rules: Export Rules Keep validation.method: full sample . Keep validation.oos ratio omitted or null . Export only supported entry families for v1: pivot breakout with vcp detection gap up continuation with gap up detection Mark unsupported hypothesis families as research only in ticket notes, not as export candidates. Guardrails Reject candidates that violate schema bounds (risk, exits, empty conditions). Reject candidate when folder name and id mismatch. Require deterministic metadata with interface version: edge finder candidate/v1 . Use dry run in pipeline before full execution. Resources skills/edge candidate agent/scripts/export candidate.py Generate strategies/<candidate id /strategy.yaml and metadata.json from a research ticket YAML. skills/edge candidate agent/scripts/validate candidate.py Run interface checks and optional StrategySpec / validate spec checks against trade strategy pipeline . skills/edge candidate agent/scripts/auto detect candidates.py Auto detect edge ideas from EOD OHLCV, generate exportable/research tickets, and optionally export/validate automatically. references/pipeline if v1.md Condensed integration contract for edge finder candidate/v1 . references/signal mapping.md Map hypothesis families to currently exportable signal families. references/research ticket schema.md Ticket schema used by export candidate.py . references/ideation loop.md Hint schema and external LLM ideation command contract.

edge-candidate-agent