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weekly-performance-digest
Use when the user wants a weekly performance summary from closed trades — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern breakdowns.
About this skill
Use when the user wants a weekly performance summary from closed trades — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern breakdowns.
SKILL.md
weekly-performance-digest.SKILL.mdPlace it in your Syntic skills folder. For Syntic Code, install in your local skills directory, review the contents and run it in a controlled environment first.
--- name: weekly-performance-digest description: Use when the user wants a weekly performance summary from closed trades — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern breakdowns. category: Performance version: 1.0.0 tools: [] --- # Weekly Performance Digest Aggregate the trades closed during a week into a single performance report — pure calculation, descriptive only, no trade recommendations. ## When to Use Use at the end of a trading week to review aggregate realized performance; to measure win rate and expectancy across all closed positions; to see which source skills, exit reasons, sectors, or mechanisms drove wins vs. losses; to feed a month-end review (combine four weekly digests) or a postmortem; or for a quick "what worked / what didn't" snapshot grounded in real closed trades. Do not use this for a single-trade deep review (use `trade-performance-coach`), for signal-level true/false-positive classification (use `signal-postmortem`), or for buy/sell recommendations or position sizing — this skill is descriptive only. ## Inputs Read CLOSED theses tracked by `trader-memory-core` for the requested date range (default: trailing 7 days). A trade counts in a week if its actual exit date falls in that range and its status is CLOSED. ## How It Works **Win/loss.** A trade with positive realized P&L is a winner, negative is a loser, zero is breakeven; win rate = winners / total trades. **R-multiple.** P&L divided by (entry price − stop-loss price) × shares, using the plan's recorded stop-loss. **Double-counting safeguard.** A CLOSED thesis's cumulative realized P&L already includes all trims plus the final leg — headline metrics use that cumulative value over CLOSED theses only. Partial trims from theses that are still open (PARTIALLY_CLOSED) are reported separately as informational and are never added into the headline totals or win rate. A position trimmed in week 1 and closed in week 2 therefore shows as a partial trim in week 1 and inside week 2's CLOSED headline — that is intended, not a duplicate. ## Workflow Compute headline metrics: win rate, expectancy, profit factor, average R-multiple, and MAE/MFE. Break results down across multiple pattern dimensions: source skill, exit reason, thesis type, sector, mechanism tag, and screening grade. Surface the week's biggest winners, losers, and process-improvement lessons. ## Output Return, in chat, a report with: - **Summary** — total trades, winners, losers, breakeven, win rate, expectancy, profit factor, total realized P&L (dollar and percent). - **Metrics** — average/largest winner and loser, average holding days for winners vs. losers, R-multiple average and standard deviation, average MAE% and MFE%. - **Pattern analysis** — win/loss breakdown by source skill, exit reason, thesis type, sector, mechanism tag, and screening grade. - **Partial trims** — count and total realized P&L from trims on still-open positions, kept separate from headline totals. - **Lessons** — top wins, top losses, and process improvements. An empty week still produces a valid report with zeroed metrics rather than an error. ## Key Principles 1. **Closed trades only for headline numbers** — cumulative outcome figures, keyed on exit date. 2. **No double-counting** — partial trims are informational and excluded from totals. 3. **Pattern attribution** — every win/loss is attributed across multiple dimensions. 4. **Descriptive, not prescriptive** — the digest reports; the user decides.
Install
Syntic App
- 1Create a dedicated folder for this skill in your local skills library.
- 2Place SKILL.md into that folder.
- 3Restart Syntic and invoke this skill on matching tasks.
Syntic Code (CLI)
- 1Save SKILL.md in your local Syntic Code skills directory.
- 2Keep related files in the same skill folder.
- 3Run in a safe environment and validate outputs.