Measure ACSets better than authors via surjectivity gadgets, Betti numbers, Möbius classification, and p-adic ultrametric distance
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概要と使いどころ
Measure ACSets better than authors via surjectivity gadgets, Betti numbers, Möbius classification, and p-adic ultrametric distance
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。
Multi-step reasoning engine for complex analysis and systematic problem solving. Use when: (1) Complex debugging scenarios with multiple layers, (2) Architectural analysis and system design, (3) Problems requiring hypothesis testing and validation, (4) Multi-component failure investigation, (5) Performance bottleneck identification. Triggers: "--think", "--think-hard", "--ultrathink", "analyze step by step", "break down this problem", "systematic analysis". IMPORTANT: Do NOT use for simple single-step tasks.
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Run the marketing harness quality gates on content. Scores Four U's (Unique/Useful/Ultra-specific/Urgent), checks for banned words and AI slop, runs SEO lint for search content. Use when "score this", "quality check", "run quality gates", "check this content", "four u's score", "banned word check", "SEO lint", or any request to validate content quality before publishing.
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Ultra-granular code analysis for deep architectural context building. Line-by-line and block-by-block analysis using First Principles, 5 Whys, 5 Hows methodology at micro scale. Builds mental models, tracks invariants and assumptions, and maps cross-function call flows for security audit preparation.
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This skill should be used to spawn specialized OpenAI Codex CLI subagents for code review, debugging, architecture analysis, security audits, refactoring, documentation, comparative evidence adjudication, and autonomous /goal runs. It adds each persona through process-local developer instructions while preserving the project's AGENTS.md chain, including during parallel launches. Supports GPT-6-Astra across low, medium, high, xhigh, max, and ultra reasoning with default or priority service tiers, plus GPT-5.6 and GPT-5.5 models. Triggers on 'delegate to Codex', 'Codex Astra', 'Astra subagent', 'Codex subagent', 'code review agent', 'security audit', 'refactor with Codex', 'goal run', 'autonomous goal', 'have Codex weigh this'.
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Systematically interpret ultraviolet-visible absorption spectra to identify chromophores, classify electronic transitions, apply Woodward-Fieser rules for conjugated systems, and perform quantitative analysis using the Beer-Lambert law.
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Navigate make-on-demand catalogues — ZINC-22 through CartBlanche and Enamine REAL Space — to find compounds that can actually be ordered. Use this skill to look substances up by ZINC identifier or structure, understand tranche partitioning by heavy-atom count and logP, and choose between screening an enumerated subset and searching a combinatorial synthon space with a fragment-growing method such as V-SYNTHES. Also trigger on ZINC22, CartBlanche, Enamine REAL, make-on-demand, tangible library, synthon, tranche, giga-scale enumeration, or ultra-large virtual screening.
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。
Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman.
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Ultra-fast proof-of-concept and MVP specialist. Use this agent when you need to validate an idea quickly working prototype before the meeting's over. Pragmatic, speed-focused, validation-oriented. Ships in days, not weeks.
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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.
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Use when a task needs the judgment of a Diagnostic Medical Sonographer — deciding whether a duplex, compression, or graded-compression ultrasound study is diagnostic versus technically limited, choosing when to interrupt a scanning protocol to escalate a real-time critical finding, setting scan technique and ALARA (TI/MI) parameters for a given exam type, or drafting the technical worksheet and preliminary findings a physician will interpret and sign.
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Use when a task needs the judgment of a Cardiovascular Technologist — measuring and grading a cardiac or vascular ultrasound finding, tracking contrast/anticoagulation/radiation limits during a live cath lab procedure, choosing between imaging modalities for a clinical question, or writing up a diagnostic study for physician sign-off.
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Use when a task needs the judgment of a Boilermaker — qualifying or selecting a welding procedure for a pressure-boundary repair, deciding whether a defect is a code "repair" or an "alteration" under the National Board Inspection Code, sizing a tube-to-drum rolled joint expansion, reading radiographic or ultrasonic weld inspection results against acceptance criteria, or setting a post-repair hydrostatic test pressure and hold time.
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Xilinx/AMD Vivado FPGA build workflow -- batch-mode TCL scripting, ADI HDL reference design integration, Zynq-7000/MPSoC block design, IP builds, synthesis, implementation, and bitstream generation. Use for any Zynq or UltraScale+ design that incorporates ADI transceivers or follows the ADI HDL reference design pattern.
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Manage energy, not just time: map your ultradian rhythms, align tasks to energy states, and design recovery. Use when time management alone isn't fixing fatigue or afternoon slumps.
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Blazing inference on Cerebras wafer-scale hardware — ultra-fast open-model APIs for speed-critical workloads.
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。
Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes.
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Treino Ultralytics YOLO pose para keypoints do campo de futebol (32 kp), export ONNX, e inferência em vídeo com vaila.soccerfield_keypoints_ai (CSV getpixelvideo + overlay). Use quando o usuário fala em football pitch keypoints, YOLO26 pose, treino Roboflow/HF dataset martinjolif, field_keypoints_getpixelvideo, calibração FIFA, ou soccerfield_keypoints_ai.
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。
Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.
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。
Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps.
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。
Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.
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。
Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes.
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。
Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman.
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。
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
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。