「document」の検索結果

Generates or updates tutorials from VHS tapes and Playwright specs with dual-tone markdown and GIF recording. Use when tutorial assets need refreshing.

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。

Merges ephemeral report and analysis artifacts into permanent documentation. Use when LLM-generated markdown files have accumulated and need consolidation.

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。

Manages digital garden notes, link structures, and health metrics. Use when curating a knowledge base, pruning stale notes, or tracking content maturity.

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。

Provides templates and lifecycle patterns for storage and documentation systems. Use when organizing knowledge storage, config lifecycle, or naming conventions.

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 a Mermaid class diagram showing types, inheritance, and composition. Use when visualizing class hierarchies or documenting a module public API.

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 a Mermaid workflow diagram showing process steps, decisions, and state transitions. Use when documenting CI/CD pipelines or lifecycle processes.

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 a Mermaid sequence diagram showing how data moves between components. Use when tracing request flows or documenting data transformation pipelines.

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。

Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.

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。

Socratic method teaching skill that guides users to discover answers themselves through questioning, never giving direct answers. TRIGGER when: user's message contains 'socratic', 'Socrates', or '소크라테스'. Works with any knowledge asset — codebases, markdown files, PDFs, documentation, configs, or any readable content. Respond in the user's language.

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。

Guides Gensim topic modelling, document indexing, embeddings, similarity retrieval, downloader, and script workflows for Python NLP and IR tasks.

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 python-doctr (docTR) for OCR/KIE inference, document IO/export, model customization, datasets/training/evaluation, CLI helpers, deployment, and troubleshooting.

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 Docling to convert, parse, configure, extract, chunk, serve, and maintain document-processing workflows across Python APIs, CLI commands, optional pipelines, and repository edits.

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 DocArray for multimodal Pydantic-style documents, typed DocList and DocVec batches, serialization and local storage, FastAPI payloads, and vector retrieval indexes.

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 design DataDesigner configs, run preview/create/validate workflows, inspect the CLI or agent context, work with plugins or MCP tools, or adapt documented recipes and integrations for synthetic dataset generation.

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。

Route DataFlow workflows for pipelines, text and document processing, serving, evaluation, and Ray acceleration.

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 Chonkie for text/document chunking, pipelines, embeddings, CLI/API serving, and storage integrations.

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。

Fast PARALLEL wiki lookup engine over wiki/techniques + wiki/payloads + wiki/tools + wiki/cheatsheets for a surface/service/vuln-class. Two modes - quick (one qmd search, cheap, fire constantly) and deep (4 parallel subagents, one per area, merged ready-to-use arsenal card, cached). This is the fast path arsenal that `arsenal` delegates to; the hunt-* skills each inline their own qmd_query and can hand off here for a parallel lookup. Use for "what do I use against <surface>", "arsenal for <X>", "deep/full arsenal", "tool + payload + technique + cheatsheet for <X>", "fast wiki lookup", "parallel wiki search", any "how do I attack/exploit <service|vuln-class>" where you want the documented tooling + payloads before hand-rolling.

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。

Triage a raw, vague issue or bug report into a structured document that names what is known, what is missing, and what to do next. Use when an incoming issue, bug report, or problem description is too vague or incomplete for investigation or planning, and recommend the right next han skill. Does not investigate root causes or trace code paths — use investigate for debugging, diagnosis, and root cause analysis. Does not plan features or build solutions — use plan-a-feature or plan-implementation for that.

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 code through a disciplined, BDD-framed Test-Driven Development loop: build a behavior test list, then drive each behavior through red-green-refactor with an enforced observed-failure gate. Use when the user wants to implement, build, or write code test-first, "do TDD", follow "red-green-refactor", drive code from tests, choose the next test by the Transformation Priority Premise (TPP) or ZOMBIES ordering, or grow a feature behavior-by-behavior with tests leading. This skill writes and changes code; it does not produce a test plan document (use automated-test-planning, or manual-test-planning for a plan a person runs by hand), review or audit existing code (use code-review), restructure existing code outside a TDD loop (use refactor, or plan-a-change to plan a multi-module restructure), specify what a feature should do (use plan-a-feature), or find the root cause of a bug (use investigate). Runs its loop to completion without pausing for review; to review each behavior as it lands, use pairing.

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。

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for planning the change its findings imply — use plan-a-change. Not for discovering bounded contexts, ubiquitous language, or where code boundaries diverge from domain boundaries — use ddd-analysis. Not for writing documentation or architectural decision records.

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。

Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-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。

Pre-contract vendor privacy due diligence per GDPR Article 28(1). Covers risk questionnaires, technical controls assessment, certification review, data flow analysis, and documented sufficiency decisions for processor engagement.

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。

Creates GDPR Article 30(2) Records of Processing Activities for data processors with all four mandatory fields: processor and controller names and contact details, categories of processing, third country transfers, and security measures description. Activate for processor RoPA, Art. 30(2), processor records, sub-processor documentation.

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。

Handles GDPR Article 21 right to object to processing, including compelling legitimate grounds assessment, ceasing processing obligations, documentation requirements, and the relationship with erasure under Article 17(1)(c). Activate for right to object, Art. 21, objection to processing, legitimate interest queries.

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。