Loading...
Loading...
Found 9,946 Skills
Project-specific environment setup for issue workflows. Calculates test ports and provides initialization context for minions.
Hand off a task to Codex CLI for autonomous execution. Use when a task would benefit from a capable subagent to implement, fix, investigate, or review code. Codex has full codebase access and can make changes.
LLM app development with RAG, prompt engineering, vector databases, and AI agents
Company newsletter and content roundup creation with consistent formatting, content curation, and audience segmentation. Use when creating internal newsletters, external digests, or content summaries.
Designs responsive interfaces starting from mobile screens with progressive enhancement for larger devices. Use when building responsive websites, optimizing for mobile users, or implementing adaptive layouts.
Searchable solution documentation system with YAML frontmatter. Builds institutional knowledge from solved problems. Use proactively when consulting past solutions before investigating new issues.
This skill should be used for multi-session autonomous agent work requiring progress checkpointing, failure recovery, and task dependency management. Triggers on '/harness' command, or when a task involves many subtasks needing progress persistence, sleep/resume cycles across context windows, recovery from mid-task failures with partial state, or distributed work across multiple agent sessions. Synthesized from Anthropic and OpenAI engineering practices for long-running agents.
Coordinates 4 documentation audit workers (structure, semantic, fact-check, code comments). Delegates parallel audits, aggregates into docs/project/docs_audit.md.
Ask Codex via local CLI and capture a reusable artifact
Ask Gemini via local CLI and capture a reusable artifact
UI design team pipeline. Research existing design system, generate design tokens (W3C format), audit quality, and implement code. CSV wave pipeline with GC loop (designer <-> reviewer) and dual-track parallel support.
Recursive codebase analysis using the RLM paradigm. Use when: analyzing large codebases (100+ files), investigating cross-cutting patterns, recursive decomposition of complex code questions, scanning for issues across entire repos. Triggers: analyze this codebase, how does X work across the codebase, scan all files for Y, recursive analysis, RLM.