Android and iOS application security testing — static and dynamic analysis, APK/IPA inspection, OWASP MASVS/MASTG verification, secure-storage and transport review, and mobile malware triage for authorized assessments
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概要と使いどころ
Android and iOS application security testing — static and dynamic analysis, APK/IPA inspection, OWASP MASVS/MASTG verification, secure-storage and transport review, and mobile malware triage for authorized assessments
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Answer a hard question by fanning it out to a PANEL of models running in parallel — each answering independently with web search and bash, none seeing the others' work — then having Opus 4.8 judge every response into a structured analysis (consensus, contradictions, partial coverage, unique insights, blind spots) and write a final answer grounded in it. The panel is two independent Opus 4.8 runs (slug opus4.8-4.8), Opus 4.8 + GPT-5.5 via codex (opus4.8-gpt5.5), Opus 4.8 + Gemini 3.1 Pro via agy (opus4.8-gemini3.1pro), or all three (opus4.8-gpt5.5-gemini3.1pro). Opus always judges and writes the final answer — the pipeline can't be reversed. Runs on local CLI subscriptions (no metered API), and saves a timestamped provenance .md per run. Use this whenever the user asks to "run it through Fusion", says /fusion, wants a multi-model / panel / ensemble answer, wants a question cross-checked across models, or wants a higher-confidence answer with consensus and blind spots surfaced — even if they don't say "fusion". General-purpose: any topic (research, law, strategy, technical, personal). Best for high-stakes research, design calls, and debugging where being confidently wrong is expensive.
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Use when an app, service, or user-mode driver host TTD recording is available and earlier calls, writes, or lifetimes matter. Not for kernel replay or history from a normal dump.
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Tear down a competitor's repo or product into a feature inventory and adoption choices. Use when: comparing us to another tool or asking what to steal.
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Use when reverse engineering tools are missing, not working, or need configuration. Installation guides for radare2 (r2), Ghidra, GDB, QEMU, Frida, binutils, and cross-compilation toolchains. Keywords - "install radare2", "setup ghidra", "r2 not found", "qemu missing", "tool not installed", "configure gdb", "cross-compiler"
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This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.
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Use when reverse-engineering or detecting malware — static triage + capa/YARA-X, emulation/DBI/.NET unpacking, dynamic/fileless/Volatility 3 memory analysis, C2 config extraction (Cobalt Strike/CAPE), C2 traffic detection (JA4+, beaconing)
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Plan, draft, audit, and publish content for Instagram. Use when the user wants to write a caption with a first-125-char hook, plan a slide-by-slide carousel, reverse-engineer the hook from a viral Reel or carousel, size hashtags the 2026 way, remove AI tells from a caption, or plan a week of Reels and carousels. Instagram requires media on every post, so the skills write the caption and the user supplies the image or video; posts publish via the Publora API draft, upload, schedule flow.
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Reverse-engineer the hook from a viral Instagram Reel or carousel, given a URL or a pasted caption. Identifies which of the 10 canonical 2026 formulas it uses (number-first, contrarian, relatable, confession, listicle, before/after, myth-buster, framework, pattern-interrupt Reel, how-I Reel), explains why it worked, names the primary goal, and returns a blank template mapped to your topic. Use to learn from a post you admire. Not for writing your own (use ig-caption-writer or ig-carousel-planner).
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Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
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Export a project's FF&E product-library CSV as dealer-system SIF. Use to produce a .sif schedule; use sif-to-csv for the reverse direction.
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Parse a SIF (Standard Interchange Format) input into a readable preview and optionally append canonical product rows to the project's CSV library. Use when asked to convert or inspect SIF dealer data. For the reverse direction use /as:csv-to-sif.
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Convenes a multi-LLM expert panel to pressure-test hard-to-reverse decisions. Use when reversibility score is low and adversarial review is warranted.
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This skill should be used when the user asks about "pantsing", "discovery write", "write without an outline", "discovery draft", "write into the dark", "story kernel", "reconcile a chapter", "dead end", "drafting sprint", "writing cadence", or wants to draft a story by discovery with retrospective bible reconciliation. NOT for outline-first drafting, or mysteries and other clue-dependent genres where setup must come before payoff (use chapter-writing), or a reverse outline of an existing linear draft, a subplot cut, or another revision pass on existing chapters (use revision-continuity).
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This skill should be used when the user asks to "revise a chapter", "continuity check", "find inconsistencies", "audit character state", "check timeline consistency", "developmental edit", "structural revision", "reverse outline", "cut a subplot", "revision passes", "what pass next", "pacing check" as a revision pass, "clue check", "cut to a word count", or "length pass", or to prepare existing story material for the next revision pass. NOT for planning book structure (use plot-structure), scene-level craft (use scene-craft), voice consistency (use voice-style), or reconciling a chapter drafted by discovery (use discovery-drafting).
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Investigate how a concept, code path, application, network flow, system, incident, document, or local artifact actually works, then deliver a two-depth visual HTML explainer with a dead-simple big-picture first layer and source-backed technical depth behind it. Use when the user invokes $xray, asks how something works under the hood, wants a module or app behavior traced across boundaries, requests web, code, network, or safe static artifact research before explanation, or asks for an evidence-backed explainer. Do not use for answer-only definitions, general web design, full codebase audits, or invasive binary reverse engineering without explicit authorization.
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对用户拥有或明确获授权的本机可执行文件、应用二进制和版本产物做只读静态逆向,包括 Claude Code 及其他 CLI、Mach-O、ELF、PE、Wasm 或打包应用。仅在用户明确要求“逆向、扒实现、查二进制字符串/符号/依赖、验证内部行为、比较两个版本”时使用;不要因普通提及软件而触发,也不要用于执行未知样本、绕过授权/计费、破解或再分发。
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Use when planning with fixed deadline or target outcome, working backward from future goal to present, defining milestones and dependencies, mapping critical path, identifying what must happen when, planning product launches with hard dates, multi-year strategic roadmaps, event planning, transformation initiatives, or when user mentions "backcast", "work backward from", "reverse planning", "we need to launch by", "target date is", or "what needs to happen to reach".
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Competitive Ad Intelligence. Analyzes competitor advertising strategies including platform identification, landing page analysis, targeting reverse-engineering, positioning gaps, creative approach evaluation, and builds a "beat the competition" strategy with a competitor ad swipe file template.
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Extract the design of a screenshot, website URL or Figma file into a design.md with tokens, components, layout and brand rules, or copy one element (navbar, card, illustration) into an element.md with a rebuild or image-generation prompt. Use when the user wants to document, replicate, audit or reverse-engineer a visual design: its design system, palette, typography or style.
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Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion (Munger: invert, always invert), and wrong_if falsifiability review. ≈50-finding cap sorted by severity; content-derived finding IDs; incremental scoping with three backstops; lifecycle hooks at pillar-complete / thesis-complete / pre-reduction.
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Think and work like an expert Computational Neuroscientist. Use when a task calls for Computational Neuroscientist judgment. Reasons from encoding/decoding, GLM/LNP spike-train likelihood, mean-field E-I balance, and neural manifolds through NEST/Brian/NEURON/BMTK, GPFA/LFADS, Brain-Score alignment, and trained-RNN reverse engineering while treating spike-sorting contamination, model non-identifiability, nested-CV leakage, and task-optimization≠mechanism as first-class failure modes.
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Think and work like an expert Cognitive Neuroscientist. Use when a task calls for Cognitive Neuroscientist judgment. Reasons from latent constructs through converging behavior, fMRI/M/EEG, TMS, and lesion evidence; designs factorial and dissociation contrasts, fMRIPrep/GLMsingle/MNE pipelines, MVPA/RSA, and COBIDAS reporting while treating pure insertion, reverse inference, motion confounds, and in-sample decoding as first-class failure modes.
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Compare gene regulatory and co-expression networks between biological conditions to identify rewired regulatory relationships using DiffCorr. Detects gained, lost, and reversed gene-gene correlations between conditions. Use when comparing co-expression networks between disease vs control, treatment conditions, or developmental stages.
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