Results for “reproducible-scoring”

Create new skills, modify existing ones, and measure their performance through iterative evaluation and benchmarking.

4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples. Use when the user runs /si:extract or asks to package a recurring solution from memory into a skill.

Create new skills, modify and improve existing skills, and measure skill performance through iterative evaluation and benchmarking.

Update or correct an existing skill file based on judge feedback or improved understanding.

A git SHA pins the transformation.

Score raw leads as HOT/WARM/COOL based on config-driven weights from agency.config.json

Deterministic pixel art upscaling using EPX/Scale2x, hq2x/hq4x, and xBR algorithms that add valid sub-pixels through pattern recognition. Activate on 'pixel art scaling', 'EPX', 'Scale2x', 'hq2x', 'hq4x', 'xBR', 'retro game upscaling'. NOT for AI/ML upscaling, photo enlargement, or simple nearest-neighbor.

SUPERSEDED by persistent-cache-gap-filling (v2.8.0). Cache data during symbol selection for instant repeat runs.

当需要在众多机会中筛选出投入产出比最高的选项，以最小化风险并最大化潜在回报时

Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.

Use when making a forward-looking claim with a checkable outcome (reply within 24h, error rate will drop, this skill will see more use) — record to state/predictions.jsonl with a review horizon so reflection can grade you later. Closes the in-the-moment double-loop.

Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples.

The choice is not about scale or sophistication.

Build lean, opinionated products using the 37signals philosophy from Getting Real, Rework, and Shape Up. Use when the user mentions "Getting Real", "Rework", "Shape Up", "37signals", "Basecamp method", "six-week cycles", "fixed time variable scope", "appetite vs estimates", "betting table", "breadboarding", "fat marker sketch", "build less", "underdo the competition", or "opinionated software". Also trigger when cutting scope to ship faster, running small teams, avoiding long-term roadmaps, or eliminating meetings. Covers shaping, betting, building, and the art of saying no. For MVP validation, see lean-startup. For design sprints, see design-sprint.

Use when implementing risk-adjusted rewards, discussing Sharpe ratio in RL training, or tuning reward components for risk awareness

OpenCLIP: An Open Source Implementation of CLIP

用于编写和编辑高质量 Skill 的参考框架：通过调用设计、信息层级、引导词与剪枝提高执行过程的可预测性。

Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable. Use when the user asks "how should I write a skill" or wants skill-writing best practices.

Reproduces failures, gathers evidence, tests hypotheses, fixes root causes, and adds regression coverage.