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.
npx skills add marian2js/trading-skills --skill post-trade-debriefgit clone --depth 1 https://github.com/marian2js/trading-skillsWrote 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.
[](https://agentmods.dev/skills/marian2js/trading-skills/post-trade-debrief)<a href="https://agentmods.dev/skills/marian2js/trading-skills/post-trade-debrief"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/post-trade-debrief/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.
<a href="https://agentmods.dev/skills/marian2js/trading-skills/post-trade-debrief"><img src="https://agentmods.dev/badge/skills/marian2js/trading-skills/post-trade-debrief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00045 | $0.00782 |
| Opus 5 | $0.00023 | $0.00391 |
| Sonnet 5 | $0.00009 | $0.00156 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
post-trade-debrief 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post Trade Debrief
Use this workflow skill when a trade has closed and the user wants one clear learning process instead of manually deciding whether to do a single-trade review, a pattern review, or both.
This workflow will not:
- grade the trade only by PnL
- skip the original plan reconstruction just because the user remembers the outcome vividly
- force pattern analysis when the sample is still too small
Role
Act like a post-trade learning gatekeeper. Your job is to reconstruct what happened, identify the real lesson, and decide whether the issue belongs in a single-trade debrief or a broader journal pattern review.
When to use it
Use it when the user wants to:
- review a closed trade end to end
- convert one trade outcome into a concrete lesson
- decide whether a mistake is isolated or part of a recurring pattern
- route the result into journal analysis only when the sample supports it
Inputs and context
Ask for:
- instrument and direction
- original thesis, entry, stop, target, and size
- actual entry, exit, and result
- whether rules were followed
- what happened around the trade, including catalyst or regime context
- whether the user suspects this trade reflects a recurring issue
Helpful but optional:
- prior review notes
- whether similar trades exist in the journal
- setup tags, timeframe tags, or catalyst tags
Use the user's materials first.
If the original plan is missing, say that clearly and keep the debrief provisional rather than inventing it.
Workflow routing
Use the smallest useful chain:
- Run
post-trade-reviewon the closed trade. - If the review exposes a recurring-looking mistake and the user has enough history, run
journal-pattern-analyzer. - If the review shows a structural flaw in the original setup, run
risk-reward-sanity-checkon the original structure. - If the review shows oversizing or poor risk budgeting, run
position-sizingon what the size should have been.
Stop the workflow once the clearest lesson and next process change are established.
What ships with it
1 file 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.
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.
- 12d ago First seen · 100 lines · 45 tokens per session scan A dd934f094521
post-trade-debrief is a skill published in the GitHub repository marian2js/trading-skills (11 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 782 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 2026-08-30.
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