Loading...
Loading...
Found 6,578 Skills
Discover, query, and analyze Israeli government open data from data.gov.il (CKAN API). Use when user asks about Israeli government data, "data.gov.il", government datasets, CBS statistics, or needs data about Israeli transportation, education, health, geography, economy, or environment. Supports dataset search, tabular data queries, and analysis guidance. Pair with the MCP servers listed below for direct tool access from your agent. Do NOT use for classified government data or data requiring security clearance.
Apply signaling theory (Spence, 1973) to analyze how agents communicate private information through costly, credible signals under information asymmetry. Use this skill when the user needs to evaluate whether a corporate action serves as a credible signal, analyze dividend or IPO signaling, assess separating vs pooling equilibria, or when they ask 'why do firms pay dividends', 'is this signal credible', or 'how does underpricing signal quality'.
Automated daily security audits for OpenClaw agents with email reporting. Runs deep audits and sends formatted reports.
Comprehensive TDD patterns and practices for all programming languages, eliminating redundant testing guidance per agent.
Generates image prompts for Seedream 5.0/4.0 (Jimeng AI), and can call the API to generate images and automatically download them to the output/ directory. Workflow: describe your idea → the agent outputs a prompt for review → user confirms → the agent runs generate.py. It covers text-to-image, image editing, multi-image fusion, character consistency, knowledge cards, posters, PPT backgrounds, e-commerce images, avatars, and group/storyboard generation. Activate this tool when the user mentions terms like seedream, jimeng, AI image generation, text-to-image, image-to-image, seedream prompt, prompt keyword, one-click image generation, knowledge card, poster design, e-commerce image, character consistency, or image generation.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
Delegate tasks to parallel worktree agents using worktrunk (wt). Use when asked to "spawn agents", "run in parallel", "delegate to worktrees", or split work across multiple Claude/OpenCode sessions.
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
Enable the GitHub CLI (`gh`) in Claude Code cloud sessions and GitHub Copilot coding agent environments. Use this skill when: (1) setting up a project so cloud AI agents can use `gh` for PRs, issues, and releases, (2) configuring setup scripts or SessionStart hooks for `gh` installation, (3) adding `copilot-setup-steps.yml` for GitHub Copilot agents, (4) troubleshooting `gh` auth failures in cloud sessions, or (5) configuring `GH_TOKEN` for headless environments. Triggers on: "enable gh", "github integration", "Claude Code cloud setup", "copilot setup steps", "gh auth in cloud", "gh not working in cloud", "setup script", or any request involving GitHub CLI access from cloud-based AI coding agents.
Regenerates documentation files (agents.md, agent-skills.md, plugins.md, usage.md) from marketplace data using Jinja templates. Use when plugins are added, updated, or removed to keep documentation in sync.
Non-interactive hunk and line-range staging with the `git-hunk` CLI. Use when a user wants atomic commits, selective staging, partial hunk staging, or an agent-safe replacement for `git add -p` or `git commit -p`, especially when `git-hunk` is available in the current repo or on `PATH`.