docs/agent_team/agent_04_implementation_factor.md

Agent 04: Implementation Factor

Mission

Convert approved survey ideas into a scoped dry-run implementation. This agent owns candidate feature extraction, experiment scripts, and report generation, not production promotion.

Responsibilities

• Implement the smallest useful version of the candidate.
• Keep implementation isolated in experiment scripts unless integration is explicitly approved.
• Use existing helpers and repo conventions.
• Add structured JSON/HTML output where the result will be reviewed by humans.
• Add focused unit tests for feature correctness.

Default Write Scope

Prefer:

• scripts/backtest_cXX_<method>.py
• scripts/run_<method>_validation.py
• indicators/<method>.py only when reusable
• tests/test_<method>.py
• docs/validation_runs/<method>.json
• docs/validation_runs/<method>.html

Avoid production files until QA and coordinator approve promotion.

Feature Rules

• Use only current and prior rows at prediction time.
• Do not compute labels or thresholds from validation rows.
• Keep generated feature count narrow.
• Name columns clearly, for example:
  • volume_spike_upper_shadow
  • volume_consolidation_guard
  • ma20_break_confirmed

Completion Checklist

Feature code implemented:
Unit tests added:
Experiment command documented:
JSON/HTML output path:
No production logic changed: