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概要と使いどころ
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。
Forge highly privileged Kerberos Ticket Granting Tickets (TGTs) to gain persistent, undetectable, and long-term administrative access across an entire Active Directory domain. Use this skill during the final stages of a Red Team operation after Domain Admin access has been achieved, simulating an Advanced Persistent Threat (APT) establishing deep persistence that survives password resets.
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, reviewing, or refactoring Rust code. Covers ownership, borrowing, error handling, async patterns, API design, memory optimization, performance, testing, and common anti-patterns. Targets Rust 1.80+ and Edition 2024. Invoke with /rust-core.
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 running background tasks with Celery - worker and broker configuration (Redis, RabbitMQ), task routing by name vs queue, chains/groups/chords, retry patterns (autoretry_for, retry_backoff), acks_late semantics, failure detection, and monitoring with Flower
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。
Implements features in vertical slices, always starting with homepage. Enforces anti-placeholder rules — no lorem ipsum, no TODO stubs, no gray boxes. Real content, real images, real interactions. TypeScript strict mode, Zod validation, and structured file organization.
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。
What every delivered app must DO — anti-placeholder, complete features, working forms, psnotify notifications, feature flags, embarrassingly-easy UX, the feature catalog.
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。
Gorgeous/cinematic requirements every delivered app's UI must meet — anti-slop premium bar, exact brand tokens, motion, logo/image quality, WCAG 2.2 visual accessibility.
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。
Copy + discoverability requirements every delivered app must meet — real-brand extraction, anti-slop voice, per-page SEO/JSON-LD, pSEO, GEO/AI-search, truth/citations, competitor floor, i18n, trust surfaces.
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 real brands (Wayback for rebuilds). Copy system, headline/CTA rules, trust surfaces, legal pages, SEO+structured data, anti-AI-slop, microcopy, DESIGN.md, W3C DTCG tokens, pSEO 5 types, GEO/AI search.
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。
Anti-AI-slop design system for distinctive, premium interfaces. Bold typography, dark-first #060610, fluid clamp() type, cascade layers + native nesting + container queries, OKLCH color, @starting-style, View Transitions API, DTCG tokens.
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 token architecture - primitive/semantic/component tiers, naming grammar, CSS custom property delivery, and DTCG build pipelines
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。
Run bounded, read-only semantic advisory sidecar passes for candidate mapping, issue triage, upstream diffs, evidence verification triage, and meta audit hints. Enforces monthly spend limits with explicit fallback to worker-luna.
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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.
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。
Post-mortem analysis of a PhysicsIntern workspace run (Claude Code, Pi, Codex, or OpenCode host). Reconstructs the trajectory from the session record — JSONL file(s) for Claude/Pi/Codex, the SQLite store for OpenCode — audits methodology adherence against the workspace's own CLAUDE.md / AGENTS.md and skill/agent prompts, checks commit discipline and flag dispositions, and assesses substantive quality. Produces a thorough evidence-anchored markdown report. Use after a workspace has been worked on to identify what went well, where the methodology slipped, and what prompts to improve.
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。
Tunes noisy detections by analyzing historical alert data to quantify false-positive sources, recommend allow-list filters and threshold adjustments, and measure precision impact. Activates for requests to tune a detection, reduce false positives, or analyze alert noise and recommend filters.
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。
Pulp musical/media time primitives, exact beat divisions, tempo and meter maps, transport-range grid projection, inline and order-preserving groove projection, coordinate randomness, streaming cursors, and quantization arithmetic.
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。
The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.
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。
FastAPI guidance — typed endpoints, Pydantic validation, dependency injection, async patterns, and production deployment.
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。
Work with text embeddings — choosing models, pooling, similarity measures, evaluation, and multilingual considerations. Use when building semantic search, clustering, or any similarity-based feature.
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。
Apply classic design patterns judiciously: when each pattern fits, modern alternatives, and anti-patterns. Use when designing object interactions or reviewing pattern usage.
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。
Compare files, text, and data effectively with diff strategies, semantic comparison, and review 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。
Split documents for retrieval effectively — fixed, semantic, structural, and hierarchical chunking with overlap tuning. Use when RAG retrieval quality depends on how documents are divided.
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。