Trader memory core

Skill xonevn-ai/xone-trading-skills/skills/trader-memory-core

Bộ "kỹ năng" (Claude Skills) hỗ trợ workflow giao dịch cho nhà đầu tư cá nhân Việt Nam có quỹ thời gian hạn chế. Mục tiêu là chuẩn hoá quy trình review thị trường, quản trị rủi ro, lập kế hoạch giao dịch, ghi nhật ký và cải tiến liên tục — không thay thế phán đoán của bạn, không đưa ra tín hiệu mua/bán.

Install

npx -y skills add xonevn-ai/xone-trading-skills --skill trader-memory-core

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Track investment theses across their lifecycle — from screening idea to closed position with postmortem. Register theses from screener outputs, manage state transitions, attach position sizing, review due dates, and generate postmortem reports with P&L and MAE/MFE analysis. Trigger when user says "register thesis", "track this idea", "thesis status", "review due", "close position", "postmortem", or "trading journal".

SKILL.md

5.5 KB, as published. Nobody here has run it

Trader Memory Core

Overview

Persistent state layer that bundles screening → analysis → position sizing → portfolio management outputs into a single "thesis object" per investment idea. Tracks what you thought, what happened, and what you learned — across conversations.

Phase 1 supports single-ticker theses: dividend_income, growth_momentum, mean_reversion, earnings_drift, pivot_breakout.

When to Use

After a screener (kanchi, earnings-trade-analyzer, vcp, pead, canslim, edge-candidate-agent) produces candidates
When transitioning a thesis from IDEA → ENTRY_READY → ACTIVE → CLOSED
When attaching position-sizer output to a thesis
When checking which theses are due for review
When closing a position and generating a postmortem with lessons learned

Prerequisites

Python 3.10+
pyyaml (already in project dependencies)
FMP API key (optional, only for MAE/MFE calculation in postmortem)

Workflow

1. Register — Ingest screener output as thesis

Read the screener's JSON output and convert to thesis using the appropriate adapter.

python3 skills/trader-memory-core/scripts/thesis_ingest.py \
  --source kanchi-dividend-sop \
  --input reports/kanchi_entry_signals_2026-03-14.json \
  --state-dir state/theses/

Supported sources: kanchi-dividend-sop, earnings-trade-analyzer, vcp-screener, pead-screener, canslim-screener, edge-candidate-agent.

Each thesis starts in IDEA status.

2. Query — Search and list theses

python3 skills/trader-memory-core/scripts/thesis_store.py \
  --state-dir state/theses/ list --ticker AAPL --status ACTIVE

Filter by --ticker, --status, or --type.

3. Update — Transition, attach position, link reports

State transition (IDEA → ENTRY_READY only):

Use thesis_store.transition(state_dir, thesis_id, "ENTRY_READY", reason) from Python.

Open position (ENTRY_READY → ACTIVE):

Use thesis_store.open_position(state_dir, thesis_id, actual_price, actual_date) — the only path to ACTIVE. Accepts optional shares and event_date (for backfilling past trades).

Close or invalidate (→ CLOSED or INVALIDATED):

Use thesis_store.terminate(state_dir, thesis_id, terminal_status, exit_reason, actual_price, actual_date). For CLOSED, delegates to close() which computes P&L. For INVALIDATED, P&L is computed if entry/exit prices are available.

Record review (any non-terminal):

Use thesis_store.mark_reviewed(state_dir, thesis_id, review_date=..., outcome="OK"|"WARN"|"REVIEW") to advance next_review_date and record alerts.

Attach position-sizer output:

Use thesis_store.attach_position(state_dir, thesis_id, report_path) to link position sizing data. Validates that the report mode is "shares" (not budget).

Link related reports:

Use thesis_store.link_report(state_dir, thesis_id, skill, file, date) to cross-reference analysis documents.

4. Review — Check due dates and monitoring status

python3 skills/trader-memory-core/scripts/thesis_review.py \
  --state-dir state/theses/ review-due --as-of 2026-04-15

List theses with next_review_date <= as_of. Use with kanchi-dividend-review-monitor triggers (T1-T5) for systematic review.

5. Postmortem — Close and reflect

python3 skills/trader-memory-core/scripts/thesis_review.py \
  --state-dir state/theses/ postmortem th_aapl_div_20260314_a3f1

Generate a structured postmortem in state/journal/. If FMP API key is available, includes MAE/MFE (Maximum Adverse/Favorable Excursion) metrics.

Summary statistics:

python3 skills/trader-memory-core/scripts/thesis_review.py \
  --state-dir state/theses/ summary

Shows win rate, average P&L%, and per-type breakdown across all closed theses.

Output Format

Thesis YAML (state/theses/)

Each thesis is a YAML file with:

Identity: thesis_id, ticker, created_at
Classification: thesis_type, setup_type, catalyst
Lifecycle: status, status_history
Entry/Exit: target prices, actual prices, conditions
Position: shares, value, risk (attached from position-sizer)
Monitoring: review dates, triggers, alerts
Origin: source skill, screening grade, raw provenance
Outcome: P&L, holding days, MAE/MFE, lessons learned

Index (state/theses/_index.json)

Lightweight index for fast queries without loading full YAML files.

Journal (state/journal/)

Postmortem markdown reports: pm_{thesis_id}.md.

Key Principles

Forward-only transitions: IDEA → ENTRY_READY → ACTIVE → CLOSED (no backtracking)
Raw provenance: All original screener data preserved in origin.raw_provenance
Atomic writes: All file operations use tempfile + os.replace
Git-tracked state: state/ directory is committed, providing audit trail
Phase 1 scope: Single-ticker theses only (pair trades and options in Phase 2)

Resources

references/thesis_lifecycle.md — Status states and valid transitions
references/field_mapping.md — Source skill → canonical field mapping
schemas/thesis.schema.json — JSON Schema for thesis validation