3,268 件 ・ 関連度順
概要と使いどころ
Systematically add a new memory-system reference to Auto_Memory's reference hub. Use when analyzing a new agent memory system, adding reference/<system>/details.md, saving prompts, or updating reference/hub/technique_map.json.
日本語の概要は準備中です。原文の説明を表示しています。
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.
日本語の概要は準備中です。原文の説明を表示しています。
Design safe recurring Codex automations with clear prompts, outputs, schedules, and gating rules.
日本語の概要は準備中です。原文の説明を表示しています。
Multilingual communication, translation, localization, and language quality skill for translating, rewriting, localizing, summarizing, tone-matching, and reviewing content across languages. Use for multi-language prompts, UI strings, documentation, cultural adaptation, terminology consistency, bilingual output, language detection, and Indonesian/English or other cross-language workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.
日本語の概要は準備中です。原文の説明を表示しています。
AI and LLM red-teaming skill for evaluating prompt injection, jailbreak, data exfiltration, tool abuse, agent hijack, RAG poisoning, model denial of service, and unsafe tool-use chains in Gemini, Claude, GPT, and open-weight models. Use to build evaluation harnesses, attack corpora, defensive guardrails, and red-team reports for AI systems you own or are authorized to test.
日本語の概要は準備中です。原文の説明を表示しています。
Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference attacks.
日本語の概要は準備中です。原文の説明を表示しています。
Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.
日本語の概要は準備中です。原文の説明を表示しています。
Detects authentication and biometric bypass vulnerabilities in mobile apps (Android/iOS). Trigger on: BiometricPrompt, LocalAuthentication, LAContext, evaluatePolicy, CryptoObject, Android Keystore, Secure Enclave, kSecAccessControlBiometryCurrentSet, userAuthenticationValidityDurationSeconds, confirmCredentials, biometric fallback, PIN bypass, passive authentication, enrolled biometrics detection, Frida hook auth, jailbreak bypass, TouchID, FaceID, fingerprint. Covers MASVS-AUTH-1/2/3.
日本語の概要は準備中です。原文の説明を表示しています。
Execute advanced LLM Jailbreaking techniques using roleplay, nested environments (virtual machines), and complex personas to completely bypass safety constraints and ethical alignments embedded in AI models.
日本語の概要は準備中です。原文の説明を表示しています。
White-box source code security review structured around OWASP ASVS 5.0 (427 verification requirements across 16 chapters). Reads and understands application source code to build a security-aware knowledge base that enriches all downstream skills. Covers: tech stack identification, route/endpoint mapping, authentication and authorization architecture, dangerous function patterns, source-to-sink data flow tracing, IaC review, dependency analysis, ASVS compliance mapping, and LLM integration security (prompt injection, tool abuse, output handling, RAG poisoning, MCP server patterns). When LLM/AI framework usage is detected, automatically reviews OWASP LLM Top 10 patterns from source code and chains into /ai-redteam with white-box context for live endpoint testing. Chains into /pentester, /threat-modeling, /web-exploit, /api-security, /cloud-security, /analyze-cve, /credential-audit, and /ai-redteam — providing white-box context that transforms black-box testing into targeted, informed assessment.
日本語の概要は準備中です。原文の説明を表示しています。
Drive a native desktop app through Interpreter's builtin-cua-driver. Use get_app_state, click/type/scroll/drag, and verify by calling get_app_state again when the user asks to operate a real desktop app, browser chrome, native dialog, menu, secure prompt, file chooser, or hidden/background window.
日本語の概要は準備中です。原文の説明を表示しています。
国内电商提示词融合工作流。用于为国内微信生意、微信视频号、朋友圈、淘宝/天猫/京东风格商品展示，生成给豆包使用的中文商品主图提示词、商品宣传图提示词、商品功能细节图提示词、朋友圈营销文案和带货短视频脚本。用户提到国内电商、大牌商品展示感、朋友圈卖货、视频号、商品图、商品宣传图、功能细节图、带货短视频脚本、营销文案、豆包提示词时使用。
日本語の概要は準備中です。原文の説明を表示しています。
CLI code review patterns. Use when reviewing CLI applications built with Commander.js, @clack/prompts, picocolors. Covers exit codes, signal handling, error messages, user experience, testing adequacy.
日本語の概要は準備中です。原文の説明を表示しています。
CLI specification planning frameworks. Use when a spec touches a command surface, an interactive flow, config precedence, exit codes, or output modes. Covers flag contracts, prompt flow design, precedence tables, exit-code taxonomy, TTY/piped/JSON output, error text, signals, and cross-platform concerns.
日本語の概要は準備中です。原文の説明を表示しています。
AI specification planning frameworks. Use when a spec touches model calls, prompts, retrieval, tool calling, agentic loops, or evals. Covers approach selection, model and provider choice, structured output contracts, loop guards, budgets, failure modes, and eval design.
日本語の概要は準備中です。原文の説明を表示しています。
LLM observability with Langfuse — OpenTelemetry-based tracing, evaluations, prompt management, datasets, and production best practices
日本語の概要は準備中です。原文の説明を表示しています。
Official Anthropic SDK patterns for TypeScript/Node.js — client setup, Messages API, streaming, tool use, vision, extended thinking, structured outputs, prompt caching, batch API, and production best practices
日本語の概要は準備中です。原文の説明を表示しています。
Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization
日本語の概要は準備中です。原文の説明を表示しています。
LangChain.js patterns for building LLM applications — chat models, LCEL chains, prompt templates, structured output, agents, tools, RAG, streaming, and LangSmith tracing
日本語の概要は準備中です。原文の説明を表示しています。
Generate web, mobile, and desktop prototypes, slides, dashboards, and editorial layouts from a single prompt using brand-grade design systems. Use when the user wants /web-prototype, /mobile-app, or /dashboard interactive HTML previews exportable to HTML, PDF, PPTX, or MP4 without Figma.
日本語の概要は準備中です。原文の説明を表示しています。
Full-featured Kling 3.0 Omni video generation skill. Covers text-to-video, image-to-video, video editing (base mode), video reference (feature mode), multi-shot generation, and audio-synced video. Includes validated API constraint rules and prompt engineering guide.
日本語の概要は準備中です。原文の説明を表示しています。
Bootstrap a new standalone skill repo under gaia-research/ from the canonical template set at gaia-research/gaia-research/templates/skill-repo/. Handles the full flow: interactive prompts for all placeholders, fetches templates via the GitHub API, substitutes values, creates the new repo (gaia-research/skill-<name>), writes README.md / SKILL.md / install.sh / .gitignore / LICENSE / powered-by-gaia.svg, makes the initial commit and pushes. Also supports update mode: re-applies the template structure to a pre-existing skill repo and opens a draft PR with the drift. Use when the user says "new skill repo", "bootstrap a skill repo", "/skill-template", "create skill-foo", "spin up a gaia-research skill repo", "template a new skill", "align skill-fuse to the template", or "/skill-template update <repo>". Requires: gh CLI (authenticated with gaia-research org access), python3, git.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze a reference video and reverse-engineer its style into a reusable Seedance 2.0 prompting template for the Novoads API. The output is a new formula file — like seedance-2-ugc.md — that captures the video's structure, pacing, camera work, edit style and tone so it can be recreated with any product, any person, in any setting. Use this whenever someone provides a video they want to use as a style reference, says "I want to make videos like this", "deconstruct this video", "turn this into a template", "analyze this style", or drops a video file and wants to recreate that format repeatedly.
日本語の概要は準備中です。原文の説明を表示しています。