trader-memory-core

trader-memory-core is a skill for Claude Code, Codex from BaggaT236/AI-Trading-Skills. It costs 96 tokens per session (3,134 once invoked), scanned A, a copy of trader-memory-core, MIT.

A persistent record for tracking an investment idea from initial screening through an open or closed position and later review.

In plain words
What is it for?
Use it to register theses, move them through lifecycle stages, attach position sizing, check review dates, and create postmortems with profit and loss analysis.
Why use it?
It keeps the reasoning, position details, deadlines, outcomes, and lessons for each idea together across conversations.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to register theses, move them through lifecycle stages, attach position sizing, check review dates, and create postmortems with profit and loss analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baggat236/ai-trading-skills/trader-memory-core
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 BaggaT236/AI-Trading-Skills --skill trader-memory-core
Clone the repo
git clone --depth 1 https://github.com/BaggaT236/AI-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.

agentmods badge for trader-memory-core

README.md
[![agentmods](https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/trader-memory-core/github.svg)](https://agentmods.dev/skills/baggat236/ai-trading-skills/trader-memory-core)
Your own site
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/trader-memory-core"><img src="https://agentmods.dev/badge/skills/baggat236/ai-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.

agentmods 80×15 button for trader-memory-core

Your own site · 80×15
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/trader-memory-core"><img src="https://agentmods.dev/badge/skills/baggat236/ai-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 3,134 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.
Origin 89% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.03134
Opus 5 $0.00048 $0.01567
Sonnet 5 $0.00019 $0.00627
Haiku 4.5 $0.00010 $0.00313

Measured 9d ago against content hash c5afc434693e, 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 11 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

This is a copy

89% identical to trader-memory-core — 78 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/trader-memory-core/SKILL.md · 275 lines

How it starts

The opening of the file, as written. The whole thing — 275 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: storethesis_store.py, ingestthesis_ingest.py, reviewthesis_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 · 275 lines

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.

  1. 9d ago First seen · 275 lines · 96 tokens per session scan A c5afc434693e

Subscribe to this mod's changes

trader-memory-core is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 96 tokens to every session and 3,134 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to trader-memory-core, differing in 78 lines, and is treated as a copy.

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