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):

python3 skills/edge-candidate-agent/scripts/auto_detect_candidates.py \
  --ohlcv /path/to/ohlcv.parquet \
  --output-dir reports/edge_candidate_auto \
  --top-n 10 \
  --hints path/to/hints.yaml \
  --export-strategies-dir /path/to/trade-strategy-pipeline/strategies \
  --pipeline-root /path/to/trade-strategy-pipeline

Create a candidate directory from a ticket:

python3 skills/edge-candidate-agent/scripts/export_candidate.py \
  --ticket path/to/ticket.yaml \
  --strategies-dir /path/to/trade-strategy-pipeline/strategies

Validate interface contract only:

python3 skills/edge-candidate-agent/scripts/validate_candidate.py \
  --strategy /path/to/trade-strategy-pipeline/strategies/my_candidate_v1/strategy.yaml

Validate both interface contract and pipeline schema/stage rules:

python3 skills/edge-candidate-agent/scripts/validate_candidate.py \
  --strategy /path/to/trade-strategy-pipeline/strategies/my_candidate_v1/strategy.yaml \
  --pipeline-root /path/to/trade-strategy-pipeline \
  --stage phase1

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.