「phi」の検索結果

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

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Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements abstract-role adversarial review with named, sourced perspectives. Use when automated review findings feel generic, when a PR has architectural or UX impact, or when the author wants pre-submit hardening beyond standard checks.

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 infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Breaks content into 1-10 cartoon-style image cards optimized for social media engagement. Use when user mentions "小红书图片", "小红书种草", "小绿书", "微信图文", "微信贴图", "image cards", "图片卡片", baoyu-xhs-images, or wants social media infographic series.

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The phishing-report triage runbook — how to check headers, links, and attachments on a reported email against {{report_query}}, classify the risk, and post a verdict with a recommended action to {{security_channel}}. Analyze and recommend only; never block, delete, or remediate.

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Static visual content across 20+ formats — diagrams, mermaid, infographics, D3 dashboards, comics, icons, wallpaper — via Nano Banana Pro (default), Nano Banana, and Flux. USE WHEN art, illustration, diagram, flowchart, infographic, header image, blog social thumbnail, visualize, generate image, mermaid, architecture diagram, comic, icon, blog art, framework diagram, D3 chart, remove background, wallpaper. NOT FOR locked house-style YouTube/channel/video thumbnails, video or animation (use Remotion), or web UI design and integrated frontend layout (use Webdesign).

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AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".

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 and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

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。

Mutation-driven test vector generation. Finds implementations of a cryptographic algorithm or protocol, runs mutation testing to identify escaped mutants, then generates new test vectors that deliberately exercise the uncovered code paths. Compares before/after mutation kill rates to prove vector effectiveness. Use when generating cryptographic test vectors, measuring Wycheproof coverage gaps, finding escaped mutants via mutation testing, creating cross-implementation test suites, or improving test vector coverage for crypto primitives.

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Evil Twin / KARMA / Mana access point methodology — rogue AP construction with hostapd-mana / wifiphisher / airgeddon, KARMA universal probe response, Mana selective probe response, captive portal phishing, deauth-driven client coercion to attacker AP, MAC randomization defeat via PNL leak analysis, post-association MITM (DNS, ARP, transparent proxy), credential capture for portal/web/SMB, and detection-evasion tactics. Use to coerce client devices onto an attacker-controlled AP, intercept their traffic, harvest credentials, or deliver payloads via captive portal.

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Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building custom exploit payloads. Maps to CWE-327 (Use of a Broken or Risky Cryptographic Algorithm), CWE-328 (Use of Weak Hash), and CWE-330 (Use of Insufficiently Random Values). Emphasizes black-box identification of vulnerable implementations before transitioning to targeted exploitation.

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Build data visualizations with declarative grammars. Use when the user needs Vega-Lite, Vega, Observable Plot, or grammar-of-graphics reasoning, especially for tabular charts that do not require bespoke rendering.

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Design geospatial and cartographic visualizations. Use when the user needs help deciding whether to use a map, choosing projections or basemaps, building choropleths or symbol maps, or implementing thematic maps, slippy maps, or geospatial interactions with D3 geo, Leaflet, MapLibre, Mapbox GL JS, Google Maps, OpenLayers, deck.gl, ArcGIS Maps SDK, Azure Maps, HERE Maps, CesiumJS, or related tools.

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Create skeuomorphic web UI surfaces with layered gradients, stacked inner and outer shadows, reflective gradient borders, micro texture, and embossed text or icon details. Use when asked for pressed, carved, tactile, realistic, soft-plastic, soft-metal, or premium physical interface styling.

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 a high-contrast clean skeuomorphic design system with molded dark surfaces, crisp light separation, tactile inset depth, and restrained signal accents.

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。

Claymorphism design system skill. Use when building soft, puffy, clay-like UI components with large radii, dual inner shadows, and offset outer shadows.

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。

Glassmorphism design system skill. Use when building frosted-glass UI components with blur, transparency, and layered depth effects.

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 modifying `resources/workflow-schema.json` in cc-wf-studio to influence how AI agents generate workflows via the cc-workflow-ai-editor skill. Triggers include "AIが特定のノードタイプを選んでくれない", "ワークフロー生成のバイアスを調整したい", "スキーマの description を変えたい", "新しいノードタイプを追加したい", "嘘の制約がスキーマに混じっていないか確認したい". Covers what the schema actually does (instructions to AI, not runtime constraints), the design philosophy (align direction, do not prescribe rules), the build pipeline (.json → .toon auto-generated), and known bias sources to audit.

Generate a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.

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Comprehensive guide for AntV L7 geospatial visualization library. Use when users need to: (1) Create interactive maps with WebGL rendering (2) Visualize geographic data (points, lines, polygons, heatmaps) (3) Build location-based data dashboards (4) Add map layers, interactions, or animations (5) Process and display GeoJSON, CSV, or other spatial data (6) Integrate maps with AMap (GaodeMap), Mapbox, Maplibre, or standalone L7 Map (7) Optimize performance for large-scale geographic datasets

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Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.

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Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.

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对比图/一图流：生成 A vs B 参数对比图、优劣势对比表、产品参数一图流。 用 HTML+CSS 渲染成可截图的视觉卡片，适合小红书/微博等平台分享。 使用时机：用户说"做个对比图"、"A vs B"、"参数对比"、"优劣对比"、 "一图流"、"对比表"、"哪个好"、"对比一下"。 和 chart-visualization 的区别：chart 做数据图表（柱状图/折线图），comparison-card 做对比表/一图流。 和 infographic 的区别：infographic 做多维信息图，comparison-card 专注 A vs B 对比。

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Use when the user asks to "analyze my target audience", "build an audience profile for influencer targeting", "research a niche community", or "deep-dive a subculture before partnering with creators"; in audience mode produces demographic/psychographic profiles, a platform-priority matrix, named personas, and an influencer-selection criteria set, and in niche mode produces a community map, culture decode (language/norms/taboos), key-voice tiers, a Brand Fit Score, and a phased entry strategy. Not for finding specific creators to contract — use influencer-discovery; not for scoring a shortlist on Suitability — use fit-scorer. 目标受众画像/人群分析 · 细分社群/亚文化调研

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。

Select, pair, and implement typefaces for web projects. Use when the user mentions "font pairing", "which typeface", "line height", "responsive typography", "web font loading", "type hierarchy", "variable fonts", "FOUT/FOIT", "typographic scale", or "the text is hard to read". Also trigger when choosing between system fonts and web fonts, optimizing font-loading performance, or designing readable long-form content. Covers readability evaluation, CSS implementation, and performance optimization. For overall UI design systems, see refactoring-ui. For dramatic typographic experiences, see top-design.

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。