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Found 2,521 Skills
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases. Triggers on: new/empty project setup for AI agents, AGENTS.md or CLAUDE.md creation, harness engineering questions, making agents work better on a codebase. ALSO triggers when users are frustrated or complaining about agent quality — e.g. 'the agent keeps ignoring conventions', 'it never follows instructions', 'why does it keep doing X', 'the agent is broken' — because poor agent output almost always signals harness gaps, not model problems. Covers: context engineering, architectural constraints, multi-agent coordination, evaluation, long-running agent harness, and diagnosis of agent quality issues.
Discover, find, compare, audit, repair, adapt, craft, run, debrief, save, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop for weak checks or unsafe authority, execute a loop with an evidence receipt, learn from completed runs, save or reuse a project loop, or validate and submit a loop to Loop Library.
Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.
Plan and run AI-agent dynamic workflows for complex tasks that benefit from explicit orchestration, goal mode, subagents or simulated work packets, approval gates, integration, verification, and reusable workflow artifacts. Use when the user invokes this skill, asks for a swarm, subagents, parallel agents, a dynamic workflow, a large migration or audit, multi-track research plus implementation, or Claude Code-style workflow orchestration.
Explore and understand Nx workspaces. USE WHEN answering questions about the workspace, projects, or tasks. ALSO USE WHEN an nx command fails or you need to check available targets/configuration before running a task. EXAMPLES: 'What projects are in this workspace?', 'How is project X configured?', 'What depends on library Y?', 'What targets can I run?', 'Cannot find configuration for task', 'debug nx task failure'.
Share to the Starchild community in two independent ways — publish a running preview to a public URL, or open-source any project's code to the community GitHub repo. Also handles fork/install/browse.
Agent onboarding for Orderly Network - omnichain perpetual futures infrastructure, MCP server, skills, and developer quickstart
Manage Blaxel resources from the command line using the bl CLI. Deploy agents, sandboxes, jobs, and MCP servers. Also installs the Blaxel CLI if not present.
End-to-end project engineering — from understanding user intent to architecture design, incremental build with verification, and systematic debugging. Covers scheduled tasks (cron jobs), dashboards, web apps, APIs, scripts, and any software the user wants built. Replaces coder + preview-dev with a unified methodology.
Use when normal web_fetch cannot read a page, when a site blocks basic fetching, or when the user needs YouTube content in AI-ready form. Guides fallback use of Firecrawl for single-page web scraping and SerpApi for YouTube search/video metadata/transcripts only.
Monitor, analyze, and optimize AWS cloud costs. Tracks spending patterns, identifies optimization opportunities, and manages budgets with alerts and recommendations.
Identity-consistent portrait generation: professional headshots, dating photos, style transfers, themed portraits, photo series, avatars, ID photos. Use when generating styled portraits from a reference photo (e.g. professional headshot, anime avatar, cyberpunk portrait, travel photo, dating profile photo, ID photo).