「aria」の検索結果

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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This skill should be used when moving from design to implementation. Triggers on "let's build", "implement this", "looks good let's code", "ready to implement". Presents options for parallel agent competition (cookoff), single subagent, or local implementation. Each agent creates own plan from shared design for genuine variation.

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。

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

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Generate a coherent, whole-paper mathematical modeling solution framework from a complete contest problem. Use after the user supplies a CUMCM or other modeling problem and asks for modeling ideas, an overall solution plan, question-by-question analysis, candidate-model comparison, model-selection reasons, innovations, validation, or cross-question linkage. For every question, explain the task and mathematical essence, compare multiple feasible models in tables, recommend a route with explicit reasons, and keep all questions connected through shared data, variables, parameters, constraints, and validation.

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Extract structured data from clinical notes with span-level provenance and null-safety. Use when users say "extract [variables] from this note", "abstract this chart", "pull structured data from these notes", "what does this note say about [field]", or when building a chart-abstraction, registry, or cohort dataset from unstructured clinical text.

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Audit applications and infrastructure handling payment card data against PCI DSS v4.0. Heavy emphasis on scope determination (the single most-leveraged variable) plus the engineering-relevant requirements — Req 3 (storage of CHD), Req 4 (transmission), Req 6 (secure SDLC), Req 7-8 (access), Req 10 (logging), Req 11 (testing), Req 12 (program). Use when the user mentions 'PCI,' 'PCI DSS,' 'PCI DSS 4.0,' 'payment card,' 'cardholder data,' 'CHD,' 'PAN,' 'PCI scope,' 'PCI compliance,' 'SAQ,' 'AoC,' 'attestation of compliance,' 'tokenization,' 'P2PE,' 'network segmentation for PCI,' or audits any system that stores, processes, or transmits payment card data.

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。

Delegate implementation and review tasks to external AI CLI tools (Codex, Gemini) with cross-model adversarial 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。

Automatic adversarial review gate that spawns 3 independent reviewers in parallel after any plan is drafted - all must PASS before presenting to user

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。

4-phase execution loop for work units - IMPLEMENT, VALIDATE, ADVERSARIAL REVIEW, COMMIT

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。

Kelly criterion optimal sizing with fractional variants, edge estimation, and practical application for crypto trading

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。

Execute multi-level exploratory testing of the app covering basic functionality, complex operations, adversarial testing, and cross-cutting scenarios, plus usability observations through a UX lens reported separately from defects. Deeper than $smoke-test. Use when the user asks to "exploratory test", "test thoroughly", "test all scenarios", "deep test", "test edge cases", "test everything", "break it", "find bugs by testing", "test usability", or "check the UX while 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。

Execute multi-level exploratory testing of the app covering basic functionality, complex operations, adversarial testing, and cross-cutting scenarios, plus usability observations through a UX lens reported separately from defects. Deeper than /smoke-test. Use when the user asks to "exploratory test", "test thoroughly", "test all scenarios", "deep test", "test edge cases", "test everything", "break it", "find bugs by testing", "test usability", or "check the UX while 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。

Analyze what changed and generate a structured test plan at .turbo/test-plans/<slug>.md covering four escalating levels: basic functionality, complex operations, adversarial testing, and cross-cutting scenarios. Use when the user asks to "create a test plan", "plan tests", "what should I test", "generate test scenarios", "test plan for this PR", or "what are the test cases".

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。

Critically assess external feedback (code reviews, AI reviewers, PR comments) and decide which suggestions to apply using adversarial verification. Use when the user asks to "evaluate findings", "assess review comments", "triage review feedback", "evaluate review output", or "filter false positives".

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。

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

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。

Configure Claude Code sandbox network isolation with trusted domains, custom access policies, and environment variables

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。

Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.

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。

Automated contract verification, detection, and remediation across multiple languages using formal preconditions, postconditions, and invariants. This skill provides both reference documentation AND execution capabilities for the full PLAN -> CREATE -> VERIFY -> REMEDIATE workflow.

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。

Query NCBI ClinVar for variant clinical significance. Search by gene/position, interpret pathogenicity classifications, access via E-utilities API or FTP, annotate VCFs, for genomic medicine.

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Deliberate-choice procedure for a medium-to-high-stakes engineering fork — when the first plausible solution (the instinct, the default next-token pull) would be costly to get wrong. Fires AUTONOMOUSLY: invoke proactively whenever a fork fits, never wait to be asked — mechanical triggers include a fix failing for the 2nd-3rd time, adding a dependency, schema/migration design, deleting or deprecating things others depend on, changing a public API, choosing an architecture or stack. Refuse the premature collapse: hold real options open (urge · contrarian · synthesis · out-of-box · intuitive dots · precedent · first-principles), ground each branch in at least one fact from outside the model (codebase, docs, benchmark, spike), future-model consequences (blast radius, reversibility, maintenance, pre-mortem), collapse by deliberate choice, then try to refute the winner before acting. Log the decision and rejected branches in docs/decision_logs/. Not for routine calls — a decision worth more than one forward pass.

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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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 attacking an AI/ML system or model — prompt injection & jailbreaks (Crescendo, Skeleton Key, Best-of-N), RAG/vector poisoning, agentic/MCP exploitation (CVE-2025-54136), ML supply-chain RCE (pickle CVE-2025-32434), model extraction / membership inference / adversarial suffixes (GCG)

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。

Amplify personality — raises layout variance and motion, strengthens typography and one signature detail, without slop. Use when the UI works but feels safe, flat, or "template-y", or when the user says "bolder", "more personality", "more creative", or "make it pop" (still professional). Invoke when the user asks for bolder on their UI, or mentions 'bolder' alongside design / UI / frontend 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。

Tone down visual noise — lowers variance and motion, simplifies layout and color weight, keeps hierarchy clear. Use when the UI feels loud, busy, or over-designed, or when the user says "quieter", "more restrained", "simpler", or "tone it down". Invoke when the user asks for quieter on their UI, or mentions 'quieter' alongside design / UI / frontend 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。