Nützliche Agent Skills, nach echter Nutzung sortiert.

fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

fastapi-patterns

FastAPI best practices covering project structure, Pydantic v2 schemas, dependency injection, async handlers, authentication, authorization, transactional service layers, and testing with httpx and pytest. Use when building or reviewing FastAPI apps — Pydantic schemas, dependencies, async handlers, auth, or tests.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

finance-billing-ops

Evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflow for ECC. Use when the user wants a sales snapshot, pricing comparison, duplicate-charge diagnosis, or code-backed billing reality instead of generic payments advice.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

flox-environments

Create reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains for any language, installing system-level dependencies (compilers, databases, native libs like openssl/BLAS), pinning exact package versions for a team, running local services (PostgreSQL, Redis, Kafka), onboarding developers with one command, or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

foundation-models-on-device

Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+. Use when adding on-device LLM features with Apple FoundationModels on iOS 26+.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

frontend-design-direction

Set an ECC-specific frontend design direction for production UI work. Use when building or improving websites, dashboards, applications, components, landing pages, visual tools, or any web UI that needs stronger product-specific design judgment.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

generating-python-installer

Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use when a Python app must ship as a minimal, fast-starting Windows installer; not for basic script-to-exe conversion. 中文触发：Nuitka 极限优化、Python 商业打包、极限编译 Python、dist 瘦身、DLL 分析、最小安装包、最快启动、商业级打包风格

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

git-workflow

Git workflow patterns including branching strategies, commit conventions, merge vs rebase, conflict resolution, and collaborative development best practices for teams of all sizes. Use when choosing a branching strategy, writing commit conventions, deciding merge versus rebase, or resolving conflicts.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

healthcare-cdss-patterns

Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows. Use when building clinical decision support — drug interaction checks, dose validation, clinical scoring, or alert severity.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

healthcare-emr-patterns

EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

healthcare-phi-compliance

Protected Health Information (PHI) and Personally Identifiable Information (PII) compliance patterns for healthcare applications. Covers data classification, access control, audit trails, encryption, and common leak vectors. Use when code touches PHI or PII in a healthcare system, or when auditing access control, audit trails, or leak vectors.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

hermes-imports

Convert local Hermes operator workflows into sanitized ECC skills and release-pack artifacts. Use when preparing a Hermes workflow for public ECC reuse without leaking private workspace state, credentials, or local-only paths.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

hexagonal-architecture

Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services. Use when introducing or refactoring toward Ports and Adapters, or when domain logic has become entangled with I/O.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

homelab-network-setup

Practical home and homelab network planning for gateways, switches, access points, IP ranges, DHCP reservations, DNS, cabling, and common beginner mistakes. Use when planning or fixing a home or homelab network — gateway, switch, AP, IP ranges, DHCP, DNS, or cabling.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

homelab-pihole-dns

Pi-hole installation, blocklist management, DNS-over-HTTPS setup, DHCP integration, local DNS records, and troubleshooting broken DNS resolution on a home network. Use when the task explicitly involves Pi-hole — installing it, managing blocklists, configuring DoH or DHCP, adding local DNS records, or diagnosing DNS resolution with Pi-hole in the path.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

homelab-vlan-segmentation

Segmenting home networks into VLANs for IoT, guest, trusted, and server traffic using UniFi, pfSense/OPNsense, and MikroTik — including switch trunk config, firewall rules, and wireless SSID mapping. Use when splitting a home network into IoT, guest, trusted, and server VLANs on UniFi, pfSense/OPNsense, or MikroTik.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

homelab-wireguard-vpn

WireGuard VPN server setup, peer configuration, key generation, split tunneling vs full tunnel routing, and remote access to a home network from mobile and laptop clients. Use when setting up WireGuard for remote access to a home network, or deciding between split and full tunnel routing.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

hookify-rules

This skill should be used when the user asks to create a hookify rule, write a hook rule, configure hookify, add a hookify rule, or needs guidance on hookify rule syntax and patterns.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

inherit-legacy-style

Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent "style drift" (the model imposing its pretrained mainstream idioms onto the project). Language- and framework-agnostic — it aligns meta-architecture only, not syntax. Once run, it becomes a behavioral constraint on all subsequent coding tasks. Do NOT use for pure research or one-off questions unrelated to code-style alignment.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

intent-driven-development

Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

investor-materials

Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

ito-baskets

Read-only Itô basket and prediction-market data skill. Index the live basket catalog, compare a basket against user-supplied research or a watchlist, build a source-grounded market brief, or draft a non-executable planning worksheet. Use when a user asks to browse or index Itô baskets, compare a basket against notes or a thesis, research prediction-market events/venues/liquidity, or plan a basket or market idea without trading. Never advises, orders, trades, reserves, or executes.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

MIT3 Dateien

ito-compute

Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, revoke device credentials, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, validate GPU nodes, revoke Itô access, or rent or purchase GPU compute and needs the supported boundary explained.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.

MIT2 Dateien

ito-inference

Inspect the availability of model serving on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed serving manifest. Use after ito-compute has booked GPU nodes and the user asks for an OpenAI-compatible endpoint, ito-serve, hosted Kimi, or self-hosted open-weights inference. ECC implements no serving stack of its own.

Installationen: 1
GitHub Stars: 253.181
Aktualisiert: 7. Sept.