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概要と使いどころ
Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.
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Design, create, inspect, update, attach, detach, preview, execute, and verify reusable Vapi Structured Outputs through public API or Server SDK workflows. Use for post-call extraction, typed call artifacts, AI-versus-regex extraction, JSON Schema design, backfilling existing calls, or retrieving structured results programmatically.
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。
End-to-end resume parsing (detect format → extract fields). Uses a combination of format detection, text extraction, and LLM parsing to normalize resume 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。
Expert knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge management.
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。
Extracts a company's tone of voice from its own content and turns it into rules a writer or an AI can follow. Phase 1 analyses 15 to 20 pages for sentence, paragraph, word and structure patterns with frequency counts; after the user reviews it, Phase 2 writes the guidelines: tone attributes with before and after examples, a We are / We are not table, tone by context, vocabulary to use and avoid, and open questions. Triggers: "tone of voice", "brand voice", "voice guidelines", "writing style guide", "extract voice from our website", "TOV". Not for visual identity (use /brand-kit) or messaging (use /messaging).
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。
Extracts a company's visual identity from screenshots (best) or its website (fallback) and writes a DESIGN.md brand file: machine-readable tokens for colours, typography, spacing, corner radius and logo usage, plus short prose explaining how and when to use each, and a list of do's and don'ts. Any later page, deck, carousel or ad can read the tokens instead of guessing. Triggers: "brand kit", "brand guidelines", "extract our brand", "design tokens", "colours and fonts from", "visual identity", "DESIGN.md". Not for tone of voice (use /tov-guidelines) or messaging (use /messaging).
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 voice patterns from existing content (website, blog, social, sales-call transcripts) and codify into voice rules. Produces voice analysis + voice guidelines (rules per pattern + violation pattern + fix template). Writes to marketing/brand/brand-voice.md as the canonical voice rules every content skill reads. Triggers - "tone of voice", "brand voice", "voice guidelines", "TOV audit", "writing rules", "extract voice"
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 visual identity from screenshots (primary) or website URL (fallback) and compile into a DESIGN.md-format brand kit — YAML token frontmatter (colors, typography, rounded, spacing, components) + 8 ordered prose sections. The YAML tokens are machine-authoritative; downstream visual skills consume them directly. Writes to marketing/brand/brand-kit.md. Triggers - "brand kit", "brand identity", "visual identity", "design tokens", "extract brand", "DESIGN.md"
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。
Core agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for malware configuration recovery, staged payload boundaries, beacon parameter extraction, and IOC decoding. Use when the user asks to recover a malware config, decode C2 or beacon fields, unpack staged payloads, extract bot or campaign IDs, or tie recovered config to observed protocol behavior under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for file uploads, imports, previews, archive extraction, format conversion, parser invocation, and deserialization chains. Use when the user asks to inspect an upload or import path, trace archive extraction, preview or converter behavior, explain how a file reaches a parser or deserializer, or connect one uploaded artifact to the decisive backend effect. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
audioFlux is a deep learning tool library for audio and music analysis and feature extraction, supporting dozens of time-frequency transforms and hundreds of feature combinations for classification, separation, MIR, and ASR tasks.
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Extracts and transforms Avro, Protobuf, and JSON Schema definitions from Confluent Schema Registry. Generates typed data models and validates schema compatibility using the Schema Registry REST API.
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Wraps Apache Tika Server REST API for extracting structured text from PDFs, DOCX, PPTX, and 1,200+ file formats. Outputs clean markdown with metadata preservation using Tika /rmeta/text endpoint and recursive parsing mode.
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Extracts text and metadata from 1000+ file formats using Apache Tika server REST API. Handles PDF OCR via Tesseract integration, Office document parsing, and email archive extraction with MIME detection.
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。
Give Claude Code a video perception layer that extracts frames, transcribes audio, and lets Claude answer questions about local videos or YouTube URLs.
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。
AgentQL is TinyFish's web automation and extraction toolkit that layers a natural-language query system on top of live sites. Its Python and JavaScript SDKs integrate with Playwright and let agents target data and interface elements without depending on brittle CSS selectors alone.
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 reusable templates from PowerPoint presentations into the template library
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。
ENS and Web3 identity resolution for XMTP agents. Use when resolving domain names, extracting mentions, or fetching Farcaster profiles. Triggers on ENS resolution, Farcaster lookup, or mention extraction.
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调用 Magic 8.3.641 执行 PD 操作：floorplan / place / DRC / layout extraction。触发场景：(1) bba-guru-pd 做 floorplan 与 placement；(2) routing 后做 DRC；(3) LVS 前 extract SPICE；(4) 显式 /bb-invoke-magic。
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 the user says 'build a design system for my site', 'extract design tokens', 'capture my brand', or 'build my style guide', or after a rebrand. Reads representative pages, theme files, and media to extract logo, colors, typography, spacing, and components, then writes a visible style-guide page.
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。
Blender MCP expert for scene inspection, Python scripting, GLTF export, and material/animation extraction. Activate when: (1) using Blender MCP tools (get_scene_info, execute_python, screenshot, etc.), (2) writing Blender Python scripts for extraction or manipulation, (3) exporting scenes to GLTF/GLB for web (Three.js, R3F), (4) debugging material or texture export losses, (5) optimizing GLB files with gltf-transform, (6) using asset integrations (PolyHaven, Sketchfab, Hyper3D Rodin, Hunyuan3D). Covers critical export gotchas, material mapping survival, texture optimization pipeline, headless CLI patterns, and known failure modes.
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 reusable components, product patterns, and design tokens into a clearer design system with shared APIs, documented defaults, and better reuse. Use when the user wants to refactor repeated UI, consolidate buttons/cards/forms/sections, build a component library, or turn one-off values into reusable tokens.
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。
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.
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。