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 clawd-aftermath/nunchi-for-aftermath --skill reflectgit clone --depth 1 https://github.com/clawd-aftermath/nunchi-for-aftermathWrote 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/clawd-aftermath/nunchi-for-aftermath/reflect)<a href="https://agentmods.dev/skills/clawd-aftermath/nunchi-for-aftermath/reflect"><img src="https://agentmods.dev/badge/skills/clawd-aftermath/nunchi-for-aftermath/reflect.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.01255 |
| Opus 5 | $0.00013 | $0.00628 |
| Sonnet 5 | $0.00005 | $0.00251 |
| Haiku 4.5 | $0.00003 | $0.00126 |
Grade A, and why
reflect-performance-review 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 8d 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 reflect-performance-review — 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REFLECT — Reflect, Evaluate, Fine-tune, Learn, Evolve, Correct, Transform
Nightly automated performance review engine. APEX runs all day — REFLECT reviews every trade at night, computing metrics, detecting patterns, and producing data-driven improvement recommendations.
Architecture
trades.jsonl → ReflectEngine.compute() → ReflectMetrics → ReflectReporter.generate() → report.md
- Load: Read trade log from
data/cli/trades.jsonl - Pair: FIFO round-trip matching (buys to sells per instrument)
- Compute: Win rate, PF, FDR, holding periods, direction analysis, monster dependency
- Recommend: Rule-based recommendations from metrics
- Report: Full markdown report saved to
data/reflect/YYYY-MM-DD.md - Distill: 3-5 line summary for agent memory
Key Metrics
| Metric | Formula | Healthy Range |
|---|---|---|
| Win Rate | winning_trades / total_trades | > 50% |
| Profit Factor (Gross) | gross_wins / gross_losses | > 1.5 |
| Profit Factor (Net) | (gross_wins - fees) / gross_losses | > 1.2 |
| FDR (Fee Drag Ratio) | total_fees / gross_wins * 100 | < 20% |
| Monster Dependency | best_trade_pnl / net_pnl * 100 | < 50% |
| Max Consecutive Losses | longest loss streak | < 5 |
Usage
hl reflect run # Review since last report
hl reflect run --since 2026-03-01 # Review from specific date
hl reflect report # View latest report
hl reflect report --date 2026-03-03 # View specific date
hl reflect history # Show metric trend over time
hl reflect history -n 30 # Last 30 reports
Agent Mandate
You are the REFLECT reviewer. Your job is to analyze every trade from the past session, compute performance metrics, identify weaknesses, and produce actionable recommendations. You run nightly — the APEX runs by day, you review at night.
RULES:
- Run REFLECT every night after trading stops — no exceptions
- ALWAYS read the full report before the next trading session
- Act on CRITICAL recommendations immediately (FDR > 30%, win rate < 35%)
- Track recommendations across reports — if the same issue appears 3+ times, escalate
- Save the distilled summary to agent memory for next-session context
- NEVER ignore FDR warnings — fees silently kill profitability
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.
- 8d ago First seen · 107 lines · 25 tokens per session scan A 2d2fd8600cf7
reflect-performance-review is a skill published in the GitHub repository clawd-aftermath/nunchi-for-aftermath (2 stars, last pushed 19d ago), licensed MIT. It adds 25 tokens to every session and 1,255 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to reflect-performance-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
reflect-performance-review
Reflect, Evaluate, Fine-tune, Learn, Evolve, Correct, Transform — nightly automated performance review.
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A repeated critical review of an economics or finance paper draft. It examines originality, evidence, research methods, literature coverage, clarity, and likely objections, using review levels from standard to especially strict.
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Use when monitor and analyze skill effectiveness in real-time. Track usage, success rates, response quality, and user satisfaction for continuous optimization. Use when monitoring and analyze skill effectiveness in real-time. track usage, success.
Indemnity and Escrow Risk Review
Use when analyzing the indemnification and escrow architecture of an M&A purchase agreement — survival, caps, baskets, escrow, and recovery mechanics — for attorney review.
reflect
A retrospective assistant for reviewing completed work, identifying lessons, and recording patterns that can be reused. A retrospective is a structured look back at what happened and what to improve.