Kaspa News — let your Claw know everything about Kaspa in one place: latest news, core development updates, ecosystem launches, community talks, and weekly reports summary. Use when someone asks what’s happening with Kaspa now, including dev/builder activity, top tweets, videos, and Reddit updates. No API keys needed.
Detects fail-open insecure defaults (hardcoded secrets, weak auth, permissive security) that allow apps to run insecurely in production. Use when auditing security, reviewing config management, or analyzing environment variable handling.
Define security policies for your workspace and audit compliance. Check installed skills against command, network, and data handling rules. Generate audit-ready compliance reports.
Full project audit — launches 5 parallel AI agents (security, bugs, dead code, architecture, performance) to scan your codebase read-only, then compiles a unified report with health grade (A+ to F) and offers surgical fixes. Language-agnostic. Zero config.
Reliable runbook for scheduled reminders and notification workflows with OpenClaw cron. Use when creating or reviewing reminder skills, scheduling one-shot or recurring reminders, choosing between systemEvent and agentTurn payloads, selecting the correct sessionTarget, writing reminder text that will still read clearly when delivered later, validating whether a job actually fired, or troubleshooting why a scheduled notification did not deliver as expected. Especially useful for ClawHub-published skills that need production-safe reminder behavior instead of ad hoc cron setup.
Control a remote Obsidian vault through Fast Note Sync. Use when reading, searching, writing, or appending notes in Obsidian from OpenClaw, especially for remote vault workflows that do not have direct filesystem access.
Turn a name into a full dossier in seconds. Feed in a name + company (or email, or LinkedIn URL) and get back a rich profile with social links, bio, company intel, recent activity, and personalized talking points. Aggregates data from multiple public sources — LinkedIn, Twitter, GitHub, company websites, news — so you can skip the manual research and jump straight to personalized outreach. Your agent does the detective work while you close deals. Supports single enrichment, batch processing, and multiple output formats (JSON, Markdown, CRM-ready). Use when researching prospects, preparing for sales calls, personalizing cold outreach, or building lead lists. Pairs perfectly with trawl for autonomous lead gen → enrichment → outreach pipelines.
Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.
Multi-agent workflow orchestrator. Use when the user asks to build, create, make, ship, develop, or launch any software (apps, webapps, websites, mobile apps, APIs, tools, bots, dashboards, SaaS, MVPs); fix or debug bugs; review or audit code; research topics; refactor code; or publish skills.
Creates new Overstory agents for Overclaw by updating all seven integration points (config, manifest, agent-def, gateway prompt, task_router, generate_agent_context, and regeneration). Supports manual creation and optional analysis from logs, TROUBLESHOOTING.md, mulch, and project tree.
Your AI's Smart Traffic Director—precisely matching OpenClaw tasks to the perfect LLM. Intelligent orchestration with OpenRouter. Security-focused: no gateway auth exposure.
Mulch Self Improver — Let your agents grow 🌱. Captures learnings with Mulch so expertise compounds across sessions. Use when: command/tool fails, user corrects you, missing feature, API fails, knowledge was wrong, or better approach found. Run mulch prime at session start; mulch record before finishing. Benefits: better and more consistent coding, improved experience, less hallucination.
Seamless bidirectional bridge between nanobot (Ollama Mistral orchestrator) and overstory (Claude Code agent swarm). Routes tasks through the OverClaw gateway (port 18800) to overstory for subagent coordination, syncs memory.
Formats SKILL.md (OpenClaw/Cursor skill docs) for optimal display on ClawHub. Produces a consistent structure—Description, Installation, Usage with benefit-focused examples, and Commands—so skill pages are clear and scannable.
Runs VirusTotal-style security checks on OpenClaw/Cursor skills before install, including remote code execution (RCE) and malicious code (obfuscation, exfiltration, backdoors). Use when evaluating a skill from a registry (e.g. ClawHub), before granting OAuth/API credentials, or when the user asks for a security review of a skill.
Manage Control D DNS filtering service via API. Use for DNS profile management, device configuration, custom blocking rules, service filtering, analytics settings, and network diagnostics. Triggers when user mentions Control D, DNS filtering, DNS blocking, device DNS setup, or managing DNS profiles.
Ethereum development knowledge for AI agents — from idea to deployed dApp. Fetch real-time docs on gas costs, Solidity patterns, Scaffold-ETH 2, Layer 2s, DeFi composability, security, testing, and production deployment. Use when: (1) building any Ethereum or EVM dApp, (2) writing or reviewing Solidity contracts, (3) deploying to mainnet or L2s, (4) the user asks about gas, tokens, wallets, or smart contracts, (5) any web3/blockchain/onchain development task. NOT for: trading, price checking, or portfolio management — use a trading skill for those.
Quality audit for merged GitCode PRs: sample by time range or repo list, check compliance (labels, comments, tests, size, etc.), output table. Use when user asks to 抽检/质量检查 已合入的 PR 规范性、多仓库 PR、或 将结果整理成表格. Multi-repo (owner/repo). Python 3.7+ stdlib only.
Generate release notes for GitCode repositories from commits (by tag range or since-date), grouped as feat/fix/docs/other, output Markdown for Release pages. 按 tag 区间或日期拉取提交并生成版本发布公告 Markdown。Python 3.7+ standard library only.
A high-performance Agent subsystem for complex multi-agent orchestration. It provides a visual workflow canvas (OASIS) to coordinate OpenClaw agents, automated computer use tasks, and real-time monitoring via a dedicated Web UI. Supports Telegram/QQ bot integrations and Cloudflare Tunnel for secure remote access.
A CLI tool that executes Python source code to manage todos via Linear's API. Creates tasks with natural language dates, priorities, and scheduling. This is a source-execution skill - code in src/linear_todos/ runs when commands are invoked.
Prevent premature completion claims, repeated same-pattern retries, and weak handoffs. Use this skill to improve verification, strategy switching, and blocked-task reporting without changing personality or tone.
DeFi Trading Engine - Autonomous DeFi trading bot with self-improving review system for OpenClaw agents. Use when setting up DeFi trading, crypto trading bot, automated trading, Base chain trading, Bankr integration, trading engine, self-improving bot, or trading strategy execution.
Shopify Theme Development Pro - Complete theme development, deployment, and design system management for OpenClaw agents. Use when building Shopify themes, writing Liquid templates, pushing theme changes, deploying to stores, or managing design systems. Triggers on Shopify theme, Liquid templating, theme development, theme deployment, push theme, Shopify design system, Online Store 2.0, theme sections.
Use when completing tasks, implementing major features, or before merging - dispatches code review subagent to catch issues before they cascade, adapted for OpenClaw sessions_spawn model
Use when encountering any bug, test failure, or unexpected behavior - enforces systematic four-phase debugging: root cause investigation, pattern analysis, hypothesis testing, and evidence-based fix verification
Use when implementing any feature or bugfix, before writing implementation code - enforces RED-GREEN-REFACTOR cycle: write failing test first, verify it fails, write minimal code, verify it passes, then refactor
Use when you have a spec or requirements for a multi-step task, before touching code - guides writing comprehensive implementation plans with bite-sized tasks, TDD, and DRY/YAGNI principles
Comprehensive ScrapeSense public API developer skill for scan orchestration, places extraction, campaign lifecycle, email cleaning, billing endpoints, and API key/webhook management. Use when implementing or debugging ScrapeSense developer flows from https://scrapesense.com/developer, building automations, validating API payloads, or packaging a developer-focused skill for ClawHub.
Transform text content into professional Mermaid diagrams for presentations and documentation. Use when users ask to visualize concepts, create flowcharts, or make diagrams from text. Supports process flows, system architectures, comparisons, mindmaps, and more with built-in syntax error prevention.
Multi-agent workflow orchestrator for coding, writing, analysis, and image tasks via tmux-driven Claude Code and Codex agents. Use when: (1) user requests a feature/fix that should be delegated to coding agents, (2) managing parallel coding tasks across front-end and back-end, (3) monitoring active agent sessions and coordinating review, (4) user says 'start task', 'assign to agents', 'swarm mode', or references the ayao-workflow-agent playbook. NOT for: simple one-liner edits (just edit directly), reading code (use read tool), or single quick questions about code.
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when (1) a command, tool, API, or operation fails; (2) the user corrects you or rejects your work; (3) you realize your knowledge is outdated or incorrect; (4) you discover a better approach; (5) the user explicitly installs or references the skill for the current task.