What is trader-memory-core?

A persistent record for an investment idea, following it from initial screening through an open or closed position and a later review. It stores the reasoning, position sizing, review dates, profit or loss, and post-trade findings.

Use it to register investment theses, move them through lifecycle stages, attach position-sizing results, check review dates, and create postmortems with profit/loss and price-movement analysis.

It keeps the history of a trade in one place instead of scattering decisions across conversations and files. This makes it easier to compare the original idea with what actually happened and capture lessons.

trader-memory-core — Skill for Claude Code and Codex by tradermonty

About the project

Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.

tradermonty/claude-trading-skills · 2,813 stars · on GitHub · tradermonty.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add tradermonty/claude-trading-skills --skill trader-memory-core

Clone the repo

git clone --depth 1 https://github.com/tradermonty/claude-trading-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/trader-memory-core/github.svg)](https://agentmods.dev/skills/tradermonty/claude-trading-skills/trader-memory-core)

Your own site

<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/trader-memory-core"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/trader-memory-core/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/trader-memory-core"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/trader-memory-core.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,237 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

Socket pass 24 May 2026
Snyk pass 24 May 2026
NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00096	$0.04237
Opus 5	$0.00048	$0.02119
Sonnet 5	$0.00019	$0.00847
Haiku 4.5	$0.00010	$0.00424

Measured 9d ago against content hash 743374df863d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

trader-memory-core scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/fmp_price_adapter.py, scripts/tests/conftest.py, scripts/tests/test_fmp_price_adapter.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

trader-memory-core — 89% identical, 78 lines differ

skills/trader-memory-core/SKILL.md · 351 lines

How it starts

The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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)
jsonschema (already in pyproject.toml; required by thesis_store.py and every command that imports it, including thesis_ingest.py and thesis_review.py)
FMP API key (optional, only for MAE/MFE calculation in postmortem)

How to invoke the CLI

Use the stdlib-only launcher trader_memory_cli.py for all CLI work. It transparently routes through uv run --project <repo> when uv is available, so the repo's pinned jsonschema is reachable even from a foreign cwd or from python3 with no global jsonschema (e.g. cron / Hermes profile runs):

# From inside the repo
python3 skills/trader-memory-core/scripts/trader_memory_cli.py store --state-dir state/theses list

# From any other cwd (cron, profile, distribution runner) — point the launcher at the repo
export CLAUDE_TRADING_SKILLS_REPO=/path/to/claude-trading-skills
python3 "$CLAUDE_TRADING_SKILLS_REPO/skills/trader-memory-core/scripts/trader_memory_cli.py" \
  store --state-dir /path/to/state/theses list

Subcommands: store → thesis_store.py, ingest → thesis_ingest.py, review → thesis_review.py. Everything after the subcommand is forwarded verbatim, so existing argument flags (--state-dir, transition, open-position, etc.) work unchanged.

Read the full file on GitHub · 351 lines

Files

What ships with it

17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 351 lines · 96 tokens per session scan A 743374df863d

Subscribe to this mod's changes

trader-memory-core is a skill published in the GitHub repository tradermonty/claude-trading-skills (2,813 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 4,237 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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