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Sf Best Pick

skill-daviddme-claude-skills-sf-best-pick · by daviddme

Pick the best StrategyFactory strategies using a multi-factor composite score (profit factor + sharpe + drawdown + recency + sample size). Use whenever the user asks "what's the best strategy on SF / pick me the top N / find me bangers / which strategies should I deploy". Returns a ranked shortlist with per-factor breakdown so the agent can explain WHY each pick made it. Read-only.

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Install

$ agentstack add skill-daviddme-claude-skills-sf-best-pick

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

sf-best-pick

The headline strategy picker. Pulls a wide HOT slice with sane quality filters, scores every candidate across seven factors, and returns the top N with a per-factor breakdown so you can explain on stream exactly why each one made the cut.

The score (each factor 0..1, then weighted)

| Factor | Weight | Floor / Target | | --------------- | ------ | ----------------------------------- | | Profit factor | 25% | 1.0 → 2.5 | | Sharpe | 20% | 0.5 → 2.5 | | Win rate | 10% | 40% → 70% | | Net profit % | 15% | 10% → 100% | | Drawdown | 15% | inverted: 30% (worst) → 8% (best) | | Recency (30d) | 10% | 0% → 15% | | Trades | 5% | 50 → 500 (sample size) |

Higher is better. A score of 0.8+ is exceptional; 0.6–0.8 is strong; below 0.5 means at least one factor is dragging hard.

When to use

  • "Pick me the top 5 strategies on StrategyFactory"
  • "Which strategies should I deploy this week?"
  • "Find me three bangers I can run on Toobit"

How to run

python sf-best-pick/pick.py \
  [--top N]                       # default 5
  [--prescreen N]                 # how many HOT to score (default 100)
  [--min-profit-factor X]         # quality floor before scoring (default 1.3)
  [--min-trades N]                # sample-size floor (default 50)
  [--max-drawdown %]              # default 25
  [--pair CSV] [--timeframe CSV]
  [--explain]                     # multi-line "why" per pick
  [--json]

Output

Table with rank, name, pair, timeframe, all the metrics, and the composite score. --explain adds a paragraph per pick: which factors lifted it, which dragged.

Notes

  • Server-side filters are used as a quality floor; the real ranking happens

client-side so the agent can adjust weights freely.

  • For market-regime-aware picking, use [sf-market-fit](../sf-market-fit/SKILL.md).
  • For deployment after picking, use [sf-deploy](../sf-deploy/SKILL.md).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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