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概要と使いどころ
Use DeepDanbooru for anime-style image tag estimation, project and Danbooru-style dataset preparation, TensorFlow training, image evaluation, TFLite conversion, and experimental Grad-CAM workflows.
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Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75% less as an image. Use when you must skim or reason over thousands of lines you will NOT edit or byte-copy. Lossy on exact strings: never for files you'll Edit, secrets, hashes, or byte-exact values. Fable-class readers only.
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。
Capture a Burp Suite Repeater request/response as a PoC image (targets/<eng>/poc/) by driving the Burp MCP + the Kali GUI. Replays a request in a Repeater tab, sends it, and grabs the request+response panes - a Burp-native PoC (client report / CTF writeup). Use when you want the evidence to come from Burp rather than a curl/terminal card, or whenever you drive a target through Burp and need the images. Pairs with hunt-burp.
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 Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
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。
Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.
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Use when packaging a Spring Boot 3 application as an OCI image or GraalVM native executable. Covers buildpacks, layered images, JVM containers, AOT hints, probes, security, and verification.
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Turn 2+ user reference images into a high-fidelity animated Codex companion using PocketMen's own local stack. Prefer the open-weight Neural Local Studio (FLUX.2 klein 4B; optional Qwen-Image-Edit-2511 Identity-Max) on compatible hardware; otherwise fall back to the deterministic local renderer. Never require hatch-pet or OPENAI_API_KEY for the normal workflow.
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Use when the user needs engineering or research-paper figures: system architecture diagrams, algorithm workflows, hardware schematics, benchmark charts, ablation plots, figure briefs, redraws, image edits, or exact publication-style plots from numeric data. Covers Gemini, Nano Banana, OpenAI image models, and local plotting workflows.
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 professional, consultant-grade PowerPoint presentations from scratch using MckEngine (python-pptx wrapper) with McKinsey-style design. Use when user asks to create slides, pitch decks, business presentations, strategy decks, quarterly reviews, board meeting slides, or any professional PPTX. AI calls eng.cover(), eng.donut(), eng.timeline() etc — 67 high-level methods across 12 categories (structure, data, framework, comparison, narrative, timeline, team, charts, images, advanced viz, dashboards, visual storytelling), consistent typography, zero file-corruption issues, BLOCK_ARC native shapes for circular charts (donut, pie, gauge), production-hardened guard rails for spacing, overflow, legend consistency, title style uniformity, dynamic sizing for variable-count layouts, horizontal item overflow protection, chart rendering, and AI-generated cover images via Tencent Hunyuan 2.0 with professional cutout, cool grey-blue tint, and McKinsey-style Bézier ribbon decoration.
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。
Write model-native Seedance 2.0 video prompts from text, images, video, or audio references. Use for text/image generation, multimodal reference, video editing, extension, track fill, or combined tasks that need stable subjects, explicit asset roles, coherent event order, camera, sound, visible text, and a 4–15 second feasibility check.
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。
Turn real product images and a verified brief into a clean Seedance 2.0 minimalist product film. Use for 4–15 second e-commerce or launch ads that require faithful product color/material/geometry, independent anchor-image roles, product-specific actions, restrained camera, readable integrated copy, sound, and a stable closing frame; not for talking-head ads or invented product features.
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Art-direct complete illustrated websites and write project-specific image-generation prompts. Use when the user requests Illustrated Gallery, a gallery-inspired visual style, or $illustrated-gallery. Covers visual direction, original artwork, and page-wide composition; not a fixed website clone, standalone image task, or generic dashboard skill.
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。
Extract color palettes from images, websites, or designs. Identifies dominant colors, generates complementary schemes, and exports in multiple formats (HEX, RGB, HSL, Tailwind, CSS variables). Use when users need color schemes from images, brand colors, or design system palettes.
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Fix SQLite "database disk image is malformed" errors caused by corrupted FTS5 indexes. Use when: (1) UPDATE/INSERT fails with "stepping, database disk image is malformed" but PRAGMA integrity_check returns "ok", (2) Only specific records fail to update while others succeed, (3) Records contain dirty text with tabs, newlines, or unusual characters that were inserted into FTS5-indexed columns. The misleading error message suggests disk corruption, but the actual issue is FTS5 index corruption from malformed text content.
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Fix false-positive Cloud Run deploys where `gcloud builds submit --tag` silently fails but the follow-up `gcloud run services update --image :latest` succeeds against a stale image, producing a confident "Deploying... Done" message with pre-fix code still live. Use when: (1) gcloud builds submit prints "ERROR: (gcloud.builds.submit) Invalid value for [source]: Dockerfile required when specifying --tag" but the shell scrolls past it, (2) code changes verified locally aren't visible in production after a deploy that printed "revision ... has been deployed and is serving 100 percent of traffic", (3) Chaining `gcloud builds submit` and `gcloud run services update` in a single copy-paste block, (4) Using the mutable `:latest` tag for Cloud Run deploys.
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Debug 404 errors for API endpoints in microservice architectures where code exists but routing sends requests to wrong service. Use when: (1) API endpoint returns 404 despite code being deployed, (2) Multiple services share same hostname via HTTPRoute/Ingress, (3) Service logs show "Health server" but you expected API endpoints, (4) Monorepo deploys multiple images and endpoint might be in different service than expected. Covers: verifying which service handles which paths, HTTPRoute path precedence, testing endpoints directly from inside cluster, matching image tags across services.
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Deploy funnelcake (api + relay) to ANY environment (production, staging, poc) on GKE via ArgoCD. Use when: (1) Deploying new funnelcake commits, (2) Building Docker images for GKE (amd64), (3) Running ClickHouse migrations, (4) Troubleshooting ImagePullBackOff errors, (5) Syncing staging/poc after production deployment. Covers complete workflow with PRE-FLIGHT CHECKLIST to prevent common deployment failures.
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Fix Gorse worker pods stuck in not-ready state due to failing health probes. Use when: (1) gorse-worker pods show 0/1 Ready but Running status, (2) Readiness probe using pgrep fails silently, (3) Worker logs show normal operation but pod never becomes ready, (4) Using zhenghaoz/gorse-worker image. The gorse-worker container is a minimal image without pgrep or ps commands, so exec-based probes using these fail.
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。
Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language. After selection, generates AI image prompts and visual briefs section-by-section. Use when the user shares content and needs visual direction, image sourcing, or creative direction for any material.
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 you need to display and browse image collections.
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 you need to upload and preview images.
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 interactive holographic cards from supplied images with colored layers, repaired scenery, signed parallax and contour glow. Use Codex native image tools with local assembly, or an explicitly selected independent API workflow.
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Convert image references into spatial hypotheses, camera constraints, construction routes, material evidence, and measurable Blender reconstruction gates. Use whenever a user asks to replicate, recreate, match, clone, or reconstruct a scene, environment, object, material, lighting setup, or shot from one or more images, especially when room connectivity, hidden space, perspective, visible-frame fidelity, material identity, aging, wetness, or photographic treatment matters.
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Create, inspect, convert, apply, replace, verify, troubleshoot, update, publish, or restore reversible CodeDrobe themes for supported Chromium/Electron AI desktop apps, including OpenAI Codex, Tencent WorkBuddy, QoderWork (CN/global), and TRAE SOLO (global/CN). Use when a user asks to turn an attached or local reference image into a Codex, WorkBuddy, QoderWork, or TRAE SOLO skin, reproduce a visual style with native UI, build a multi-app theme, work with .codedrobe-theme packages or theme images, analyze a live CDP DOM snapshot, repair DOM compatibility failures, use a custom port or installation path, capture verification screenshots, search the CodeDrobe store or install a store theme by name, publish or submit a theme to the CodeDrobe store, or migrate a legacy .codex-theme file.
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。