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概要と使いどころ
OS command injection occurs when user input is passed unsanitized to a system shell via dangerous APIs: Java `Runtime.exec()`, Python `os.system/subprocess`, PHP `system/shell_exec/exec/proc_open`, C `system/exec`. Detect via pipe `|`, semicolon `;`, `&&`, `||`, backtick, `$()` operators, and time-delay payloads (`sleep 5`). Tools: Commix, Burp Suite, OWASP WebGoat.
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 and implement Malleable C2 profiles in Cobalt Strike to evade network intrusion detection systems (NIDS/IPS) and endpoint detection architectures. This skill focuses on molding the Beacon's HTTP/HTTPS traffic to resemble legitimate network traffic like Amazon, Google, or jQuery.
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。
Generates NeMo Guardrails Colang (.co) files and YAML config blocks from a plain-language description of a chatbot's purpose, allowed behaviors, and constraints. Use this skill whenever a user wants to build guardrails for a chatbot, define allowed intents for an LLM, create an AI firewall with NeMo Guardrails, generate Colang flow definitions, or configure a semantic allow-list for a bot. Trigger this skill even when the user just describes what their bot should and shouldn't do — generating the Colang and YAML is almost always what they need next.
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。
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。
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。
Headless rich text editor framework built on ProseMirror. Use when building an editor with TipTap — setup, extensions, custom nodes and marks, menus, node views, serialization.
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。
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。
Builds a stylized 3D animated ad on the Novoads REST API as a STORYBOARD: four to six beats, each rendered from its own key frame, narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's beat formulas (anthropomorphized problem character, protagonist reveal, mascot mechanism scene, composited end card). Use for ANY Pixar-style, Disney-style, 3D animated or animated-film-look ad at ANY length: "Pixar style ad", "3D animated ad", "animated movie look", "cute 3D character ad", "a quick animated ad", "15 second animated ad", "30 second animated ad", "storyboard ad", "several scenes", "animated ad with a voice-over", "little mascots", or a product URL or photo for an emotional animated spot. No one-call tier, so ffmpeg is required. Not for stop-motion clay (use claymation-ad), talking-head UGC (novoads-api), video cloning, or static image ads.
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。
Builds a hand-sculpted stop-motion CLAY ad on the Novoads REST API as a STORYBOARD: five to eight beats, each rendered from its own key frame, a storyteller narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's arc (named protagonist, inciting moment, social beat, quiet despair, sculpted clay infographic, discovery, transformation, resolution card), and also recreates a found clay ad by reading the reference video locally with ffmpeg and Whisper. Use for ANY clay or stop-motion ask at ANY length: "claymation ad", "stop-motion ad", "clay ad", "a quick clay ad", "plasticine characters", "make an ad like this clay one", or a reference video with sculpted clay characters in it. There is no one-call tier here, so ffmpeg is required. Not for the smooth 3D animated look (use pixar-ad, which covers every Pixar-style length), talking-head UGC (novoads-api), or a static image ad.
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。
Reverse engineers ARM/AArch64 malware by identifying the architecture and instruction set state (ARM/Thumb), parsing ELF/Mach-O ARM headers, and orienting analysis around the ARM calling convention. Activates for requests to reverse ARM binaries, analyze AArch64 malware, or handle ARM/Thumb instruction-set decoding.
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Carves injected PE images and position-independent shellcode from a memory dump or carved region, identifies the payload type, and prepares it for disassembly or emulation. Activates for requests to recover injected code, carve shellcode from memory, or reconstruct a dumped payload for analysis.
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。
Uses capa to identify malware capabilities from a binary: running rule-based detection over disassembly, mapping matched capabilities to MITRE ATT&CK and MBC, and interpreting results to focus deeper analysis. Activates for requests to run capa, generate a capability report, or map a sample's behaviors to ATT&CK automatically.
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。
Analyzes position-independent code and shellcode by identifying GetPC/PEB-walk techniques, API-hash resolution loops, and relocation-free addressing so the payload can be disassembled at the right base. Activates for requests to analyze position-independent code, identify PIC techniques, or understand how shellcode resolves APIs without imports.
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。
Search, inspect, plan, apply, remove, pack, and scaffold local Pulp package manifests. Use for Pulp-native source/UI/template kits and for untrusted or semi-trusted manifest-bearing artifacts that must be reviewed before project mutation.
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。
Convert between LaTeX and Microsoft Word for academic manuscripts in either direction, and assemble .tex from mixed sources. Fires on: converting .tex/LaTeX to Word/.docx ("tex to docx", "latex to word", "tex2docx", "convert to word", "pandoc convert"); converting .docx manuscripts to LaTeX for editing and back ("convert to latex", "manuscript", "footnotes", "reference doc", the docx-to-tex-to-docx round-trip / academic paper editing pipeline); high-fidelity delivery where plain pandoc loses tables, mangles cross-references, or fails on custom macros — booktabs/regression tables, OMML equations, cleveref, \estauto, \@@input, \thanks, TikZ, native Word tables, longtable, siunitx; and building .tex from mixed PDF/docx/LLM-generated sources. Replaces and reroutes the retired skills manuscript-editing-template-latex, latex-to-docx-fidelity, tex2docx, and latex-from-mixed-sources.
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 reviewing or improving frontend accessibility, semantic structure, keyboard support, focus management, ARIA labels, screen reader behavior, WCAG 2.2 issues, touch accessibility, or assistive-technology regressions; Chinese triggers include accessibility, accessibility, a11y, WCAG, screen reader.
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 clean, graphics-first technical presentations and posters with logical slide progression, visual hierarchy, purposeful motion, and complementary speaker notes. Use for research talks, conference slides, seminars, defenses, posters, or figure-focused presentations.
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Use when a task needs the judgment of a tenure-track/tenured Education Professor in a teacher-preparation program — designing a licensure course unit against InTASC/CAEP standards, deciding whether a candidate's borderline edTPA score needs a targeted or full retake, triaging a failing student-teaching placement, or assembling CAEP self-study evidence for reaccreditation.
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Use when a task needs the judgment of a Costume Designer — deciding build vs. rent vs. buy for a specific garment, budgeting a production's costume-shop spend across principals and ensemble, engineering a quick-change to hit a scripted time window, building or reading a costume plot to track pieces across a run, or diagnosing why a build is behind schedule going into tech week.
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Use when a task needs the judgment of a Business Intelligence Analyst — reconciling a metric discrepancy between reports, designing a dimensional model or semantic layer for self-service dashboards, setting a data freshness/latency SLA, or diagnosing why a dashboard's aggregate number is misleading.
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Use when a task needs the judgment of a carpenter's helper — cutting and staging lumber to a carpenter's layout marks, assembling and standing framed wall panels, running a material take-off and waste calculation for a framing package, or recognizing when a jobsite condition (a missing guardrail component, a nail-gun trigger setting, a header that doesn't match the plan) is a stop rather than a workaround.
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 a task needs the judgment of an atmospheric scientist/operational meteorologist — interpreting ensemble forecast guidance, deciding whether conditions cross a severe-weather warning threshold, calibrating a raw model probability against verification climatology, or writing a forecast discussion or warning product under time pressure.
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。