技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: insight

英文目录

Repository for Project Insight: NLP as a Service

320
Stars
59/100
信任
分类: ml-automation审计

A comprehensive set of 38 marketing skills and 5 commands for Claude Code covering SEO/GEO and influencer marketing with evaluation frameworks.

2.6K
Stars
86/100
信任
分类: productivity审计

Every API has a secret identity. This finds it, absorbs every feature from every competing tool, then builds the GOAT CLI — designed for AI agents first, with SQLite sync, offline search, and compound insight commands.

4.0K
Stars
70/100
信任
分类: agent-frameworks审计

Tianji: Insight into everything, Website Analytics + Uptime Monitor + Server Status. not only another GA alternatives

3.0K
Stars
83/100
信任
分类: growth-marketing审计

This MATLAB and Simulink Challenge Project Hub contains a list of research and design project ideas. These projects will help you gain practical experience and insight into technology trends and industry directions.

2.1K
Stars
76/100
信任
分类: robotics-iot审计

Turn project work into reusable knowledge — an AI-agent skill for Claude Code & Codex

196
Stars
73/100
信任
分类: utility审计

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.

34K
Stars
77/100
信任
分类: research审计

Python Computer Vision & Video Analytics Framework With Batteries Included

837
Stars
71/100
信任
分类: robotics-iot审计

A SKILL.md-based agent skill covering the full deep learning experiment lifecycle—running jobs on owned or rented GPUs, verifying results, and delivering reproducible figures and tables.

62
Stars
70/100
信任
分类: research审计

Secure AI conversations with documents, video, audio, and more. Personal workspaces for focused context, group spaces for shared insight. Classify docs, reuse prompts, and extend with modular features.

138
Stars
66/100
信任
分类: rag-knowledge审计

LinkedIn-native long-form article and newsletter writing workflow for LinkedIn and Google-to-LinkedIn topic discovery, business-depth research, professional thought leadership, evidence-led drafting, final humanization, discussion design, SEO settings, auditing, and publish-ready packaging. Use when creating, outlining, researching, enriching, rewriting, humanizing, auditing, or packaging LinkedIn Articles, LinkedIn newsletters, LinkedIn long-form posts, LinkedIn thought leadership, LinkedIn B2B articles, LinkedIn 长文, LinkedIn 专栏, LinkedIn 话题调研, LinkedIn 商务内容, 去 AI 化编辑, or LinkedIn 发布包.

483
Stars
63/100
信任
分类: security审计