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概要と使いどころ
401/403 bypass playbook. Use when encountering access-denied responses on admin panels, API endpoints, or restricted paths. Covers path manipulation, HTTP method tampering, header injection, protocol downgrade, and automated bypass tools.
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。
Bypass the Windows Antimalware Scan Interface (AMSI) using memory patching, reflection, and obfuscation techniques. Execute undetected PowerShell, VBScript, JScript, and .NET assemblies in-memory without triggering Microsoft Defender or third-party AV/EDR solutions. Use this skill during Red Team engagements when loading offensive tools (Mimikatz, Rubeus, SharpHound) in memory on defended Windows endpoints.
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。
Decompile, analyze, and reverse engineer Android applications (APKs). Utilize tools like JADX, Apktool, and dex2jar to extract source code (Java/Kotlin), analyze manifest configurations (Intents, Activities), and identify hardcoded secrets or insecure API endpoints.
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。
API reconnaissance and documentation review playbook. Use when discovering endpoints, schemas, versions, OpenAPI specs, hidden docs, and surface area for API 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。
Exploit AI assistants equipped with web-browsing capabilities or internal API plugins to perform Server-Side Request Forgery (SSRF). This skill details injecting prompts that force the LLM to request sensitive internal endpoints, such as underlying cloud metadata services or internal networks.
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。
Systematically discover hidden Application Programming Interfaces (APIs), uncover undocumented endpoints (Shadow APIs), and fuzz parameters. Use this skill as the pivotal first step in API Bug Hunting, transforming a basic frontend application into a vast mapped attack surface.
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。
Orchestrates implementation of all tasks for a feature using an agent team. Respects task dependencies, runs tasks in correct order, parallelizes independent tasks. Does NOT build, run tests, or commit at any point — verification is delegated to the caller (typically `/start-job`, which runs `build-verify` and `pr-review uncommitted` afterwards). Use when the user says "implement all tasks", "run the task sequence", "implement the feature", or wants to execute multiple tasks from a task list end-to-end.
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。
Create, inspect, and edit editable PowerPoint (`.pptx`) decks with local code execution. Use for slide decks, presentations, speaker notes, charts, tables, images, and layout-sensitive presentation work.
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 or revise Interpreter UI for non-developers with an ultra-minimal, utilitarian style inspired by the OpenAI website and ChatGPT, not the developer platform. Use when simplifying settings, onboarding, chat, forms, empty states, or helper copy; when removing extra containers, labels, or visual noise; when replacing technical wording with plain language; when clarifying hierarchy and making the main user action obvious; when making every visible label and status understandable to an average HR admin or other non-technical user; when hiding implementation details such as logs, IDs, endpoints, paths, or protocol names; or when a screen must respect the app's existing CSS variables and light/dark theme 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。
Operate a logged-in Miaoshou ERP workflow for TikTok Shop Malaysia product discovery, product screening, profit estimation, listing preparation, and reviewed publishing. Use when the user asks to search or select products in 妙手 ERP, evaluate low-price traffic products, prepare Malaysian TikTok Shop listings, move products into the TikTok collection box, or publish approved listings. Prefer browser operation through the user's existing login; never store credentials or call undocumented private endpoints.
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。
Use when building cross-platform desktop apps with PyQt6 or PySide6 - hub for installation, project structure, signals and slots basics, and pointers to widgets, styling, dialogs, threading, and testing sub-skills
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。
Use when building Django REST APIs with django-ninja - Pydantic schemas, routers, CRUD endpoints, authentication, pagination, file uploads, async views, OpenAPI docs, or migrating from DRF
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。
Use when writing or reviewing error handling, floating-point math, concurrent code, remote calls, singletons/globals, hot-path data structures, or high-volume log statements
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。
Unistyles 3.0 styling - C++ powered StyleSheet superset with zero re-renders, theming, breakpoints, variants, dynamic functions, runtime values
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。
Qdrant vector database -- collection management, point operations, payload filtering, named vectors, quantization, recommendations, snapshots
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。
Local LLM inference with the Ollama JavaScript client -- chat, streaming, tool calling, vision, embeddings, structured output, model management, and OpenAI-compatible endpoint
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。
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation, audio transcription, translation, summarization, and Inference Endpoints
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。
Serverless GPU compute platform for AI model deployment — web endpoints, GPU functions, model serving, and TypeScript client patterns
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。
Together AI SDK patterns for TypeScript — client setup, chat completions, streaming, structured output, function calling, embeddings, image generation, fine-tuning, and OpenAI-compatible endpoints
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。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
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。
Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.
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。
Fixed-topology, discovery-only extension for Gaia curation. Atomically checkpoints each candidate transition, retries only the failed field, and stops at human L4 review.
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。
Close out a review/meta branch that lands an evidence-ingest / curation batch: create the named nodes, ingest verified evidence, appraise Trust Magnitude, calibrate stars, wire suites, correct upstream naming, stage ONLY the intended artifacts (dropping CRLF churn and blocking leaks), validate, and open the PR. Use when a curation/ingest batch is verified and ready to land, or when the user says "close the review/meta branch", "land the ingest batch", "wrap up the intake PR", "/gaia-review-meta-close". Wraps the deterministic hygiene in scripts/review_meta_close.py and gates the judgment calls (calibration, Origin, suite promotion, naming, merge) behind explicit human checkpoints.
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。
Burn timed, styled captions into a finished video on the local machine, without re-rendering the source. This is the manual fallback to the API's captioning endpoint, POST /v1/captions, which stays the default path: come here when the style the user wants is outside the API's presets, when the wording has to be hand-corrected before it is burned into the pixels, or when the source was rendered with audio disabled and the API refuses it. Transcribes the audio with Whisper, groups words into reading phrases, renders the captions in a real browser via HyperFrames, and composites them over the source with ffmpeg using a real alpha channel. Use when the user has an MP4 with speech and asks to add captions, subtitles, burned-in text, TikTok-style captions or word-by-word text to it, and the API path has been ruled out. Runs out of band, so it costs no credits and works on any video file whoever generated it. Not for generating video (use the video skills) and not for a separate .srt/.vtt sidecar file.
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。