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Found 6,684 Skills
Read and search Mattermost chat using the `mm` CLI. Use this skill whenever the user mentions Mattermost, chat messages, team chat, unread messages, DMs, channel history, mentions, or wants to catch up on what happened in chat. Also triggers when the user asks about specific people's messages, channel activity, searching for something someone said, or checking notifications. The CLI outputs agent-friendly JSON by default with thread IDs, bot detection, and channel refs - no parsing needed.
Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from Cypress/Selenium, sync with TestRail, run on BrowserStack. 55 templates, 3 agents, smart reporting.
Execute on-chain trading actions via the Zerion CLI: swap, bridge, and send tokens across 14 EVM chains and Solana. Use whenever the user asks to swap / trade / convert tokens, bridge across chains, or transfer tokens to an address. Always uses an API key + agent token (no pay-per-call). Pair with `zerion-agent-management` to set up tokens/policies first, and `zerion-analyze` to check positions before trading.
This skill should be used when the user asks to "chat with AI", "ask Olly", "ask the agent", "send message to AI", "continue a chat", "follow up on chat", "get artifact", "download artifact", "list artifacts", "retrieve generated content", "AI-generated charts", "AI analysis", "conversational observability", "natural language query", or wants to interact with the Coralogix Observability Agent (Olly) using the cx CLI.
Use when a PR is submitted and ready for peer review, to evaluate another agent's work against task requirements and code quality standards
How to author a content brief that actually guides a writer (human or AI) to produce a piece that ranks, converts, or both. Per-piece editorial brief: target keyword and cluster, search intent, audience and JTBD, heading structure, entity coverage for AEO/GEO, internal linking strategy, success criteria. The middle path between thin briefs (a keyword and a deadline) and thick briefs (a 4-page document nobody reads). Triggers on content brief, brief the writer, brief the article, brief authoring, content brief template, brief audit, per-piece brief, editorial brief, target keyword brief, search intent brief. Also triggers when briefing a human writer or an AI agent on a single content piece.
Maintain repository integrity and documentation. Use for auditing structure, checking config validity, and reviewing inventory. Use proactively to validate the repository or sync documentation. Examples: - user: "Validate the repo" → run audit_repo.py - user: "Check agents" → run audit_repo.py, review errors - user: "Update documentation" → run sync_docs.py - user: "Check for issues" → run full audit
A complete workshop curriculum for building an agentic application using the Gemini Interactions API. Guides the user from basic API calls to a full production coding agent.
Implement account linking using StackOne Connect Sessions and the Hub React component. Use when user asks to "connect a provider", "embed the integration picker", "add BambooHR to my app", "create a connect session", "set up auth links", or "handle account webhooks". Covers the full flow from session creation to webhook handling. Do NOT use for making API calls after linking (use stackone-platform) or building AI agents (use stackone-agents).
Systematic GitHub Actions workflow authoring skill for AI coding agents. Analyzes repositories to determine project type, language ecosystem, and deployment targets, then generates production-grade CI/CD workflows with proper security hardening, caching, and optimization. Handles greenfield projects (no workflows exist), brownfield updates (modify, optimize, secure existing workflows), and workflow audits with workflow-specific guidance for each. Use when the user requests GitHub Actions workflows: CI pipelines, CD deployments, release automation, scheduled jobs, or any .github/workflows YAML authoring. Also use when existing workflows need auditing, optimizing, securing, or restructuring. Triggers on phrases like "set up CI", "add CI/CD", "GitHub Actions workflow", "release automation", "deploy on tag", "publish to npm/PyPI", "schedule a job", "cron workflow", "matrix build", "workflow.yml", "actions/checkout", "permissions", "harden this pipeline", "pin actions to SHA", "OIDC", "least privilege", "supply-chain", "audit my workflows", "speed up CI", or "cache dependencies". Triggers when creating or editing files under `.github/workflows/`, `action.yml`/`action.yaml` (composite or Docker actions), or `.github/dependabot.yml`. Triggers when the user mentions migrating from GitLab CI, CircleCI, Travis, Jenkins, Drone, or Buildkite to GitHub Actions. Do NOT use for non-GitHub CI systems (GitLab CI, CircleCI, Jenkins) unless the user is migrating TO GitHub Actions. Do NOT use for general bash scripting, Makefiles, or local-only build configuration.
Analyze an in-progress git branch, compare it with the current master/main using a subagent, derive practical lessons, and generate a concise redo handoff. Use when restarting a messy branch, redoing work cleanly, extracting lessons from current changes, or preparing another agent to verify the handoff, align with the user, and rebuild from the default branch.
Write a high-quality prompt for any LLM or AI assistant — Claude, Claude Code, ChatGPT, Gemini, Cursor, Windsurf, Copilot, or any coding / chat agent. Use this skill whenever the user asks to write, improve, refine, shorten, or rewrite a prompt; asks "how should I phrase this for [model]" or "what's a good prompt for [task]"; describes a task they want an AI to do but hasn't yet formulated it as a prompt; or pastes an existing prompt and asks for revision. Based on Boris's (Anthropic, Claude Code creator) prompt methodology — short and accurate prompts, plan-before-code, feedback loops, persistent context in files. The universal principles (short, plan-first, feedback-loop, no-padding) apply to any LLM; the Claude-Code-specific anchors (CLAUDE.md, @file, slash commands) only apply when the target is Claude Code. If the user's intent is unclear (target model, deliverable, scope, or whether the AI has a way to self-verify is missing), ask 1–3 targeted clarifying questions via AskUserQuestion before writing the prompt.