Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.
原样镜像官方 Codex 桌面应用:每 15 分钟探测、SHA256 可校验、国内直连下载、 Mac 可增量更新 | Verbatim, verifiable mirror of the official Codex desktop app — probed every 15 min, with a Sparkle delta-update feed.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.
Quick start: pip install jsoniq ⛈️ RumbleDB 2.1.0 "Cedrus Libani" 🌳 for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more
Run a <400ms latency Voice Agent on just 4GB VRAM. Fully offline, no API keys required. Optimized for GTX 1650 and edge robotics with zero-copy inference. (Apache 2.0)
Codex skill for curating GitHub starred repositories into safe, meaningful GitHub Stars Lists.
Python Toolkit For Quantitative Trading
A pack of AI agent skills for interacting with Sendmux email service, including sending emails and managing credentials.
End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.
Analyze a GitHub Actions integration test run and produce a skill invocation report with failure root-cause issues. TRIGGERS: analyze test run, skill invocation rate, test run report, compare test runs, skill invocation summary, test failure analysis, run report, test results, action run report
Draft and stress-test a VISION.md for a repository, then iterate with the author on an interactive review board until approved. Use on /vision or when asked to create or refine a project vision.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.
原样镜像官方 Codex 桌面应用:每 15 分钟探测、SHA256 可校验、国内直连下载、 Mac 可增量更新 | Verbatim, verifiable mirror of the official Codex desktop app — probed every 15 min, with a Sparkle delta-update feed.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.
Quick start: pip install jsoniq ⛈️ RumbleDB 2.1.0 "Cedrus Libani" 🌳 for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more
Run a <400ms latency Voice Agent on just 4GB VRAM. Fully offline, no API keys required. Optimized for GTX 1650 and edge robotics with zero-copy inference. (Apache 2.0)
Codex skill for curating GitHub starred repositories into safe, meaningful GitHub Stars Lists.
Python Toolkit For Quantitative Trading
A pack of AI agent skills for interacting with Sendmux email service, including sending emails and managing credentials.
End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.
Analyze a GitHub Actions integration test run and produce a skill invocation report with failure root-cause issues. TRIGGERS: analyze test run, skill invocation rate, test run report, compare test runs, skill invocation summary, test failure analysis, run report, test results, action run report
Draft and stress-test a VISION.md for a repository, then iterate with the author on an interactive review board until approved. Use on /vision or when asked to create or refine a project vision.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.
原样镜像官方 Codex 桌面应用:每 15 分钟探测、SHA256 可校验、国内直连下载、 Mac 可增量更新 | Verbatim, verifiable mirror of the official Codex desktop app — probed every 15 min, with a Sparkle delta-update feed.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.
Quick start: pip install jsoniq ⛈️ RumbleDB 2.1.0 "Cedrus Libani" 🌳 for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more
Run a <400ms latency Voice Agent on just 4GB VRAM. Fully offline, no API keys required. Optimized for GTX 1650 and edge robotics with zero-copy inference. (Apache 2.0)
Codex skill for curating GitHub starred repositories into safe, meaningful GitHub Stars Lists.
Python Toolkit For Quantitative Trading
A pack of AI agent skills for interacting with Sendmux email service, including sending emails and managing credentials.
End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.
Analyze a GitHub Actions integration test run and produce a skill invocation report with failure root-cause issues. TRIGGERS: analyze test run, skill invocation rate, test run report, compare test runs, skill invocation summary, test failure analysis, run report, test results, action run report
Draft and stress-test a VISION.md for a repository, then iterate with the author on an interactive review board until approved. Use on /vision or when asked to create or refine a project vision.
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.
原样镜像官方 Codex 桌面应用:每 15 分钟探测、SHA256 可校验、国内直连下载、 Mac 可增量更新 | Verbatim, verifiable mirror of the official Codex desktop app — probed every 15 min, with a Sparkle delta-update feed.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.
Quick start: pip install jsoniq ⛈️ RumbleDB 2.1.0 "Cedrus Libani" 🌳 for Apache Spark | Run queries on your large-scale, messy datasets (JSON, text, CSV, Parquet, Delta...) | Data Lakehouse with Updates, Scripting, Declarative Machine Learning and more
Run a <400ms latency Voice Agent on just 4GB VRAM. Fully offline, no API keys required. Optimized for GTX 1650 and edge robotics with zero-copy inference. (Apache 2.0)
Codex skill for curating GitHub starred repositories into safe, meaningful GitHub Stars Lists.
Python Toolkit For Quantitative Trading
A pack of AI agent skills for interacting with Sendmux email service, including sending emails and managing credentials.
End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.
Analyze a GitHub Actions integration test run and produce a skill invocation report with failure root-cause issues. TRIGGERS: analyze test run, skill invocation rate, test run report, compare test runs, skill invocation summary, test failure analysis, run report, test results, action run report
Draft and stress-test a VISION.md for a repository, then iterate with the author on an interactive review board until approved. Use on /vision or when asked to create or refine a project vision.