Agents
AI agents and automation
agentic-engineering
by affaan-m
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
agent-harness-construction
by affaan-m
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
agent-builder
by n8n-io
Load before calling build-agent for a new or existing n8n Agent. Governs prerequisite creation, faithful handoff of the user's request, agent targeting across turns, builder questions, testing, and publishing. Use directly for routine follow-ups when the conversation already targets an Agent; rerun intent-recognition only when the requested artifact is no longer clear.
n8n:create-skill
by n8n-io
Guides users through creating effective Agent Skills. Use when you want to create, write, or author a new skill, or asks about skill structure, best practices, or SKILL.md format.
debugging-executions
by n8n-io
Debug failed or wrong-output workflow executions using executions tools. Load when the user reports execution failures, unexpected node output, empty parameter values after a successful run, or a node showing a red or failed expression error.
config-evals
by n8n-io
Builds and maintains configuration-based evaluations on a workflow with the eval-config tool. Use when the user asks to set up, add, view, change, or remove an evaluation, score, grade, or judge a workflow's output, or measure answer quality against a test dataset. This is the only eval form Instance AI handles — it does not touch on-canvas evaluation nodes.
agent-setup-maintenance
by langfuse
Shared workflow for editing Langfuse's repo-owned agent setup under .agents/. Use when changing AGENTS files, shared skills, .agents/config.json, generated shim behavior, provider discovery paths, or install-time agent sync.
create-repo-agent
by langfuse
Design, implement, review, or harden Langfuse repo-owned autonomous agents. Use for LLM-powered GitHub Actions, scheduled or dispatched agents, agent-created PRs, prompts, allowlists, tokens, untrusted content, or self-updating instructions.
dogfood
by callstack
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.
agent-device
by callstack
Automates Apple-platform apps (iOS, tvOS, macOS), Android devices, and Amazon Vega OS TV apps in Vega Virtual Devices. Use when navigating apps, taking snapshots/screenshots where supported, driving TV remotes, tapping, typing, scrolling, extracting UI info, collecting evidence, or planning agent-device CLI commands.
connector-review
by open-metadata
Review an OpenMetadata connector against golden standards. Runs multi-agent analysis covering architecture, code quality, type safety, testing, and performance. When a PR number is given, automatically posts the quality summary to the PR description and a detailed review as a PR comment.
ops-automation-agent
by mastra-ai
Authoring playbook for building agents that automate recurring internal tasks — running scheduled workflows, syncing data between systems, posting notifications, processing inbound events, or executing operational runbooks. Use this when the user wants an agent that runs on a schedule, reacts to events, automates a process, syncs between tools, or handles ops/internal infrastructure.
spreadsheet-agent
by mastra-ai
Authoring playbook for building agents that read or write tabular data — Google Sheets, Microsoft Excel, CSV, Airtable, Notion databases, or any spreadsheet. Use this when the user wants an agent that updates rows, reads cells, computes totals, generates reports from sheets, syncs data between spreadsheets, or automates anything involving rows, columns, ranges, or worksheets.
Agent Development
by anthropics
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
agent-signal
by lobehub
'Build or extend LobeHub Agent Signal pipelines. Use for signal sources, signal/action types, policies, middleware, workflow handoff, dedupe, scope behavior, or observability.'
agent-testing-bot
by lobehub
Bot-channel end-to-end verification for LobeHub — drives the real native chat apps (Discord / Slack / Telegram / WeChat / Lark / QQ / iMessage) via osascript or the iMessage bridge, on macOS. Extends the generic acceptance skill for bot surfaces. Triggers on 'test bot', 'bot test', 'test in discord', 'test in telegram', 'test in slack', 'test in wechat', 'test in weixin', 'test in lark', 'test in feishu', 'test in qq'.
heterogeneous-agent
by lobehub
'Implement or debug LobeHub heterogeneous agents. Use for Claude Code/Codex adapters, external CLI agents, event mapping, IPC, persistence, tool-call chains, sessions, traces, or adapter bugs.'
agent-runtime-hooks
by lobehub
'Agent runtime lifecycle hooks. Use for before/after tool or step hooks, tool mocks, human intervention, sub-agent calls, context compression, evals, callAgent, or lifecycle events.'
herdr
by ogulcancelik
"Control herdr from inside it. Manage workspaces and tabs, split panes, spawn agents, read output, and wait for state changes — all via CLI commands that talk to the running herdr instance over a local unix socket. Use when running inside herdr (HERDR_ENV=1)."
agent-memory-systems
by sickn33
"Memory is the cornerstone of intelligent agents. Without it, every
ai-agent-development
by sickn33
"AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents."
ai-ml
by sickn33
"AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features."
agent-orchestration-multi-agent-optimize
by sickn33
"Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability."
agent-framework-azure-ai-py
by sickn33
"Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK."