Loading...
Loading...
Found 3,472 Skills
Modern Python 3.12+ patterns your AI agent should use. Type hints, async/await, Pydantic v2, uv, match statements, and project structure.
Generate a personalized portfolio site from agent-reference reports and deploy it to GitHub Pages. The site reflects the user's working style as observed by their AI collaborators — AI analyzes the reports, proposes a design concept, scaffolds an Astro site with concept-based theming, and deploys to {username}.github.io. Use this skill whenever the user asks to "build my portfolio", "create portfolio site", "make a site from my reports", "deploy to github pages", "github.io site", or says things like "포트폴리오 사이트 만들어줘", "사이트 배포해줘", or wants to turn agent-reference reports into a live website. Also triggers when the user has agent-reference reports ready and wants to publish them as a site, wants a personal site generated from AI collaboration data, or asks to update/redeploy an existing agent portfolio. Do NOT use for general Astro development, generic website building, agent-reference analysis without site generation, or resume writing that does not involve deploying a site.
Generates high-quality Gherkin (BDD) scenarios from functional requirements using a two-agent iterative cycle: a generator agent that creates/modifies the Gherkin and a reviewer agent that validates it and proposes improvements. The cycle repeats automatically until the Gherkin passes review. Use this skill whenever the user mentions: "generate Gherkin", "BDD scenarios", "Gherkin test cases", "Feature/Scenario/Given/When/Then", "requirements to Gherkin", "BDD specifications", or asks to transform functional requirements into behaviour tests. Also applies when the user brings a requirements document and wants test cases, acceptance criteria, or user stories with executable examples.
Audit skill SKILL.md files for compliance with the agentskills.io specification. Checks frontmatter fields (name, description, compatibility, metadata, argument-hint) and metadata sub-fields (author, scope, confirms). Use when adding new skills, reviewing skill quality, or ensuring all skills follow the spec. Triggers: "audit skills", "check skill spec", "skill compliance", "are my skills up to spec", "/claude-skill-spec-audit".
Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.
Skill to create custom agents for VS Code Copilot or OpenCode, helping users configure and generate agent files with proper formatting and configurations. Use when users want to create specialized AI assistants for VS Code Copilot (.agent.md files) or OpenCode (JSON/markdown agent configs) with specific tools, prompts, models, and behaviors. If the user is not specific about the target platform, ask them to specify Copilot or OpenCode.
Persistent cross-session task queue for AI agents using Claude Code Tasks schema. Add, claim, complete, and reassign tasks with move-based locking, dependency tracking (blocks/blockedBy), conversation transcript linking, and staleness detection. Use for: (1) saving tasks for future agent sessions, (2) cross-session task persistence, (3) multi-agent task coordination, (4) linking conversation transcripts to tasks. Triggers: task queue, save task, agent task, queue task, persistent task, cross-session task, task for agent.
Modern Git command best practices for AI agents. Use modern, purposeful commands introduced in Git 2.23+ instead of legacy multi-purpose commands. Teaches when to use `git switch` (branch operations), `git restore` (file operations), and other safer alternatives to improve clarity and reduce errors.
Build AI agents and automate Claude Code programmatically using the Claude Agent SDK and headless CLI mode. Use this skill when you need to build an agent, create a Claude agent, make a bot, work with the agent SDK, run Claude in headless mode, write programmatic agent code, automate with Claude, create an MCP server builder, or query Claude programmatically. Covers the Python SDK, the claude -p headless interface, custom tool creation with SDK MCP servers, hooks for deterministic control, session management, and CLI flag reference. Authentication uses existing ~/.claude/ config — no API keys required.
Technical guide for creating a new Paperclip agent adapter. Use when building a new adapter package, adding support for a new AI coding tool (e.g. a new CLI agent, API-based agent, or custom process), or when modifying the adapter system. Covers the required interfaces, module structure, registration points, and conventions derived from the existing claude-local and codex-local adapters.
Provides strategic insights on AI-driven software democratization and agent-based development trends from Replit's perspective. Use when discussing the future of software engineering, AI agent infrastructure requirements, democratization of coding, or when analyzing how AI will transform software creation from expert-only to universal access. Triggers include questions about software engineering automation trends, agent sandbox environments, SWE-bench benchmarks, or strategic implications of AI coding assistants for startups and enterprises.
Use when creating cloud sandboxes (microVMs) to run code, start dev servers, and generate live preview URLs. Also covers deploying AI agents, MCP servers, batch jobs, and Agent Drives (shared filesystems) on Blaxel's serverless infrastructure. Reach for this skill when you need isolated compute environments, real-time app previews, shared file storage across sandboxes, or to deploy agentic workloads.