trade-journal

trade-journal is a skill for Claude Code, Codex from nimadorostkar/Claude-Skills-collection. It costs 39 tokens per session (1,402 once invoked), scanned A, original, MIT.

A structured record for writing down trades, the reasoning behind them, and what happened afterward.

In plain words
What is it for?
Recording entries and exits, reviewing performance, finding patterns across trades, tracking adherence to a plan, and turning findings into rule changes.
Why use it?
It separates the quality of the decision from the result, making recurring mistakes and rule violations easier to identify.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Recording entries and exits, reviewing performance, finding patterns across trades, tracking adherence to a plan, and turning findings into rule changes.

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Install with agentmods
npx agentmods add skills/nimadorostkar/claude-skills-collection/trade-journal
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 nimadorostkar/Claude-Skills-collection --skill trade-journal
Clone the repo
git clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collection

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 trade-journal

README.md
[![agentmods](https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/trade-journal/github.svg)](https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/trade-journal)
Your own site
<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/trade-journal"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/trade-journal/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 trade-journal

Your own site · 80×15
<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/trade-journal"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,402 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
  • 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.01402
Opus 5 $0.00019 $0.00701
Sonnet 5 $0.00008 $0.00280
Haiku 4.5 $0.00004 $0.00140

Measured 9d ago against content hash d08a50574c23, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

trade-journal 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.

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.

skills/finance/trade-journal/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Trade Journal

Purpose

Learn from your own decisions rather than from your outcomes. A profitable trade taken against your rules is a bad trade that will be repeated; a losing trade taken correctly is a good one. Without a journal, these are indistinguishable.

When to Use

  • Recording a trade at entry.
  • Reviewing performance over a period.
  • After a losing streak, to determine whether the process or the market changed.
  • Identifying recurring mistakes.

Capabilities

  • Structured trade recording: thesis, plan, execution.
  • Process-versus-outcome separation.
  • Pattern identification across trades.
  • Rule-adherence tracking.
  • Converting findings into rule changes.

Inputs

  • The trades: entry, exit, size, and — crucially — the reasoning at the time.
  • The plan as it was stated before the outcome was known.
  • Market context.

Outputs

  • A record that permits honest review.
  • Identified patterns, not anecdotes.
  • Specific rule changes with a date.

Workflow

  1. Record the thesis before the outcome — At entry, in writing: why, where the stop is, where the target is, and what would prove the thesis wrong. Written afterwards, this is a rationalization, and it will be a flattering one.
  2. Grade the process, not the profit and loss — Did you follow your rules? That is a binary question with a clear answer, and it is the only one you control.
  3. Categorize by setup and by mistake — Not by outcome. "Chased an extended entry" is a category. "Lost money" is not.
  4. Review a sample large enough to be meaningful — Twenty trades minimum. Any five trades can be attributed to anything.
  5. Look for the pattern, not the story — Are the losses concentrated in one setup? One time of day? Trades taken after a loss? These are behavioral patterns and they recur.
  6. Change one rule, and date it — Then measure whether it helped. Changing five rules at once means learning nothing.

Best Practices

  • The most common and most costly journaling error is writing the thesis after the outcome is known. Memory is not merely imperfect; it actively reconstructs the past to justify the present.
  • Grade every trade against the rules, independently of whether it made money. A rule violation that was profitable is the most dangerous event in trading, because it is reinforced.
  • Look for the revenge trade: the position taken immediately after a loss, larger than the rules permit, in a setup you would normally skip. It is nearly universal and it is visible in the data.
  • Track the trades you did not take. A rule that keeps you out of losers is doing its job, and it is invisible without a record.
  • Screenshot the chart at entry. Your memory of what the setup looked like will drift toward whatever justifies the outcome.
  • A journal you do not review is a diary. The review is the entire point.

Read the full file on GitHub · 130 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 · 130 lines · 39 tokens per session scan A d08a50574c23

Subscribe to this mod's changes

trade-journal is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 39 tokens to every session and 1,402 once invoked, about $0.0002 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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