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Found 1,897 Skills
Umbrella router for Graphistry workflows across SDK and API surfaces. Use to dispatch between Python SDK, REST API, and (future) JavaScript SDK workflows.
Comprehensive technology stack blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks, programming languages, and implementation patterns across multiple platforms (.NET, Java, JavaScript, React, Python). Generates configurable blueprints with version information, licensing details, usage patterns, coding conventions, and visual diagrams. Provides implementation-ready templates and maintains architectural consistency for guided development.
Generate Python RSS feed scrapers from blog websites, integrated with hourly GitHub Actions
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
Production incident response procedures for Python/React applications. Use when responding to production outages, investigating error spikes, diagnosing performance degradation, or conducting post-mortems. Covers severity classification (SEV1-SEV4), incident commander role, communication templates, diagnostic commands for FastAPI/ PostgreSQL/Redis, rollback procedures, and blameless post-mortem process. Does NOT cover monitoring setup (use monitoring-setup) or deployment procedures (use deployment-pipeline).
LangChain workflows for `create_agent`, LCEL chains, `bind_tools`, middleware, and structured output with production-safe orchestration. Use when implementing or refactoring LangChain application logic in Python or TypeScript.
Design, build, run, and test Restate durable services, virtual objects, workflows, and AI agents across TypeScript, Python, Java, and Go. This skill should be used when the user mentions "restate", "durable execution", "virtual object", "restate service", "restate workflow", or "durable agent" or wants to build resilient backend services, AI agents, or workflows with automatic failure recovery. Also use when converting existing applications or migrating from workflow orchestrators to Restate. Use proactively when a project contains restate dependencies in package.json, requirements.txt, pyproject.toml, pom.xml, build.gradle, or go.mod.
Apply Clean Architecture + DDD + Hexagonal patterns to backend services. Use when designing APIs, microservices, domain models, aggregates, repositories, bounded contexts, or scalable backend structure. Triggers on DDD, Clean Architecture, Hexagonal, ports and adapters, entities, value objects, domain events, CQRS, event sourcing, repository pattern, use cases, onion architecture, outbox pattern, aggregate root, anti-corruption layer. Language-agnostic (Go, Rust, Python, TypeScript, Java, C#).
Configures and runs LLM evaluation using Promptfoo framework. Use when setting up prompt testing, creating evaluation configs (promptfooconfig.yaml), writing Python custom assertions, implementing llm-rubric for LLM-as-judge, or managing few-shot examples in prompts. Triggers on keywords like "promptfoo", "eval", "LLM evaluation", "prompt testing", or "model comparison".
Use this skill when building applications with Gemini models, Gemini API, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript), model selection, and API capabilities.
Professional PDF solution. Create PDFs using HTML+Paged.js (academic papers, reports, documents). Process existing PDFs using Python (read, extract, merge, split, fill forms). Supports KaTeX math formulas, Mermaid diagrams, three-line tables, citations, and other academic elements. Also use this skill when user explicitly requests LaTeX (.tex) or native LaTeX compilation.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.