Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Uses Alibaba HappyHorse 1.0 through inference.sh for text-to-video, image-to-video, reference-to-video, and natural-language video editing. Supports character preservation and videos up to 15 seconds at 720p or 1080p for product demos and social content.
Provides text-to-video prompting and schema guidance for HappyHorse 1.0. Covers synchronized audio, character consistency across shots, language support, duration, aspect ratio, resolution, and alternative model selection.
Guides HappyHorse 1.0 video generation with synchronized audio and character consistency across shots. Covers multilingual prompts, duration, aspect ratio, resolution, and selection of alternative video models.
Covers synchronized audio, 1080p output, character consistency across shots, and multilingual prompts. Provides duration, aspect ratio, and resolution guidance, plus routing advice for alternative video models.
Provides a decision framework for situations with no appealing options. Applies 10/10/10 analysis and regret minimization to choices such as layoffs, down rounds, or ending a product line.
Evidence-based read-only detection of production hardcode across frontend and backend languages: user-visible strings bypassing i18n, fixed API responses, endpoints/hosts, tenant or environment values, placeholder content, and static business data. Use for requests to find hardcoded text/data/config, i18n bypasses, magic production values, or backend/frontend literals without treating every string…
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready.
Hardware interfacing and peripheral management for Zephyr RTOS. Covers the sensor subsystem (channels, triggers, fetch/get), pin control (Pinctrl) and multiplexing, GPIO management using Devicetree specs, and SoC-level hardware configurations. Trigger when adding new hardware components, configuring pinmux, or developing sensor-based applications.
Inspects active configuration, diagnoses ignored rules, and ports configuration between hosts. Adds guides, skills, hooks, tests, and CI sensors to improve development and runtime harnesses.
Creates and improves agent instruction files, feature and state tracking, verification gates, session handoffs, and persistent memory. Addresses context budgets, scope boundaries, tool permissions, and multi-agent coordination to improve coding-agent reliability across sessions.
Orchestrator for agent harness work — the setup that makes AI agents follow project rules and improve when they fail. FIRES PROACTIVELY when agents misbehave, repeat mistakes, ignore instructions, skip skills, or when AGENTS.md exists but docs/harness/manifest.json is missing. Also triggers on: harness engineering, agent scaffold, agent keeps failing, agent not following instructions, make agents …
Improve agent reliability over time — diagnose why agents fail and fix the setup. Triggers on: agent keeps failing, same mistake again, agent not improving, make agent smarter, agent quality plateau, agents ignore skills, agent skips tests, fix agent behavior, agent unreliable, improve agent setup, self-improving harness, agents worse over time, tune agent instructions, agent going in circles, age…
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name