Direktori skill

Temukan skill yang dapat digunakan kembali untuk AI agents.

Cari skill GitHub nyata berdasarkan tugas lalu periksa stars, trust, audit, kategori, dan jalur pemasangan sebelum digunakan.

Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.

Hasil pencarian: marked

Direktori bahasa Inggris

A markdown parser and compiler. Built for speed.

37K
Stars
77/100
Kepercayaan
Kategori: document-processingAudit

Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds", "case summary", or "patient presentation".

90K
Stars
80/100
Kepercayaan
Kategori: design-creativeAudit

A curated collection of field-tested, reusable skills for Hermes Agent, covering operational workflows like inspect, diagnose, recover, migrate, and verify.

123
Stars
77/100
Kepercayaan
Kategori: utilityAudit

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

34K
Stars
77/100
Kepercayaan
Kategori: data-analysisAudit

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

34K
Stars
70/100
Kepercayaan
Kategori: researchAudit

A toolkit providing reusable slash commands, hooks, and templates for bootstrapping AI-agent-friendly projects with a self-improvement loop.

79
Stars
66/100
Kepercayaan
Kategori: coding-agentsAudit

A spec-driven development and code quality toolkit for AI coding agents, installable via npm and integrated with multiple agent harnesses.

39
Stars
70/100
Kepercayaan
Kategori: coding-agentsAudit

A portable skill for offline, local-only context migration across coding agent sessions.

35
Stars
68/100
Kepercayaan
Kategori: coding-agentsAudit

A collection of Claude Code skills for ML research tasks including paper writing, citation verification, and experiment tracking.

14
Stars
66/100
Kepercayaan
Kategori: researchAudit

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.

282
Stars
69/100
Kepercayaan
Kategori: coding-agentsAudit