Skill-Verzeichnis

Wiederverwendbare Skills für AI Agents entdecken.

Durchsuche reale GitHub-Skills nach Aufgabe und prüfe Stars, Trust, Audit, Kategorie und Installationspfad vor der Verwendung.

Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.

Suchergebnisse: marked

Englisches Verzeichnis

A markdown parser and compiler. Built for speed.

37K
Stars
77/100
Trust
Kategorie: 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
Trust
Kategorie: 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
Trust
Kategorie: 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
Trust
Kategorie: 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
Trust
Kategorie: 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
Trust
Kategorie: 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
Trust
Kategorie: coding-agentsAudit

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

35
Stars
68/100
Trust
Kategorie: coding-agentsAudit

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

14
Stars
66/100
Trust
Kategorie: researchAudit

Builds and designs React Native Nitro Modules with Nitrogen, HybridObject TypeScript specs, Nitro View components, generated native implementations, zero-copy and native-state APIs, Swift/Kotlin/C++ bindings, example apps, and testing. Use when creating a Nitro Module, adding or reviewing HybridObjects, building a Nitro View (HybridView) component, designing Nitro-specific public APIs, implementing native functionality, or setting up the nitrogen codegen pipeline. Pair with api-design for general library API shape.

161
Stars
69/100
Trust
Kategorie: researchAudit