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 BaggaT236/AI-Trading-Skills --skill trade-performance-coachgit clone --depth 1 https://github.com/BaggaT236/AI-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/baggat236/ai-trading-skills/trade-performance-coach)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/trade-performance-coach"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/trade-performance-coach/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/baggat236/ai-trading-skills/trade-performance-coach"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/trade-performance-coach.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 | $0.00097 | $0.01921 |
| Opus 5 | $0.00048 | $0.00960 |
| Sonnet 5 | $0.00019 | $0.00384 |
| Haiku 4.5 | $0.00010 | $0.00192 |
Grade A, and why
trade-performance-coach 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 13d 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.
This is a copy
100% identical to trade-performance-coach — 0 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Performance Coach
Overview
Trade Performance Coach reviews recorded trade outcomes and journal evidence to help a human trader improve their decision process. It converts closed-trade records, postmortem findings, risk rules, and optional market-regime context into an evidence-based coaching report covering:
- process adherence
- risk discipline
- execution quality
- possible trading-behavior patterns
- next-session operating rules
- coach questions for reflection
This skill is intended to fill the support role that a risk manager, desk lead, or trading coach might provide in a professional trading environment. It is strictly a process-review skill: it never recommends entering, exiting, buying, selling, shorting, holding, or sizing a specific security.
When to Use
Use this skill when any of the following are true:
- A trade has been closed and the user wants a post-trade coaching review.
- A partial close occurred and the user wants to inspect sizing, stop, or exit behavior.
- The user has
trader-memory-corethesis records andsignal-postmortemfindings and wants next-session operating rules. - The user wants a monthly review of recurring process, risk, execution, or behavior patterns.
- The user asks for a risk-manager style review of their own recorded trades.
- The user asks whether a loss was a process error, execution error, market environment issue, or acceptable variance.
- The user wants possible FOMO, revenge-trade, overconfidence, hesitation, stop-moving, or size-creep patterns flagged with evidence.
When Not to Use
Do not use this skill to:
- Pick stocks or rank trade candidates.
- Approve or reject a live trade as financial advice.
- Place orders or draft broker instructions.
- Provide therapy, mental-health diagnosis, or personality assessment.
- Infer private psychological traits beyond the trade evidence supplied.
- Shame the user for losses or rule violations.
- Replace
trader-memory-core; this skill consumes journal/thesis records and produces coaching findings.
What ships with it
15 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.
- assets/performance_coach_report.schema.json 5.1 KB
- references/behavior-tags.md 3.2 KB
- references/hermes-integration.md 1.5 KB
- references/output-contract.md 2.1 KB
- references/review-framework.md 3.6 KB
- references/risk-review-checklist.md 1.9 KB
- scripts/review_trade_performance.py 30 KB runs code
- scripts/tests/fixtures/incomplete_record.json 254 B
- scripts/tests/fixtures/monthly_aggregate_revenge_pattern.json 878 B
- scripts/tests/fixtures/partial_close_stop_moved.json 997 B
- scripts/tests/fixtures/risk_data_missing_no_size_creep.json 880 B
- scripts/tests/fixtures/single_trade_clean_loss.json 970 B
- scripts/tests/fixtures/single_trade_premature_exit.json 1020 B
- scripts/tests/fixtures/single_trade_rule_violation_loss.json 1.0 KB
- scripts/tests/test_review_trade_performance.py 7.7 KB runs code
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.
- 13d ago First seen · 255 lines · 97 tokens per session scan A fab5075390be
trade-performance-coach is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 97 tokens to every session and 1,921 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to trade-performance-coach, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
ib-pmcc-advisor
Analyze PMCC (Poor Man's Covered Call / diagonal spread) positions from IB portfolio. For each diagonal spread, reports short leg risk (delta, IV, assignment probability), daily P&L projections, top-3 roll candidates, and a side-by-side comparison table. Requires TWS or IB Gateway running locally.
scanner-pmcc
Scan stocks for Poor Man's Covered Call (PMCC) suitability. Analyzes LEAPS and short call options for delta, liquidity, spread, IV, yield, trend direction, and earnings proximity. Use when user asks about PMCC candidates, diagonal spreads, or LEAPS strategies.
ib-stop-loss
Downside stop-loss management for PMCC, naked LEAPS, and stock positions in IB. Computes stop prices, detects alerts, and places conditional combo orders. Dry-run by default. Requires TWS or IB Gateway running locally.
ib-trailing-stop
Server-side trailing stop management for stocks and naked LEAPS in IB. Places native TRAIL orders that auto-ratchet the stop as price climbs. Dry-run by default. Requires TWS or IB Gateway running locally.
stock_analyzer
A stock and market analysis skill that returns structured information about trends, prices, news, risks, catalysts, and possible trading plans.
ib-collar
Generate tactical collar strategy reports for protecting PMCC positions through earnings or high-risk events. Requires TWS or IB Gateway running locally.