「ingest」の検索結果

7z 压缩包解压工具。递归扫描目录内 .7z 文件及分卷（.7z.001 等），解压并输出解压清单。依赖 py7zr 库。不负责 zip、rar 等其他格式的解压。

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。

ZIP 压缩包内容预览工具。递归扫描目录内 .zip 文件，列出内部文件清单并按需输出文本片段预览，供后续采集流程判断是否需要解压处理。 当用户提到 zip 预览、压缩包内容查看、zip 文件清单、压缩包预检等需求时使用此 skill。 即使用户没有明确说出"zip 预览"，只要任务涉及在解压前先查看 zip 压缩包内部文件结构和内容片段，就应该使用此 skill。 不负责 7z、rar、tar 等其他压缩格式的预览（各有独立 skill），也不负责解压或归档打包。

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 a `source-tutorial` workspace has ingested sources and needs a grounded tutorial contract before structure planning.

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。

Fetch and normalize supported source-tutorial inputs into local, traceable text artifacts.

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 `paper-review` needs a canonical manuscript text artifact before claim extraction.

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 and maintain the user's local LLM Wiki from any Codex or Claude Code conversation or project. Use when the user asks to search personal knowledge, recall prior research or decisions, answer from the wiki, create durable notes, ingest a source into the wiki, update topic/concept/entity/question pages, write back useful answers, or run wiki lint/reindex 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。

Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports both local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also supports AI-based comprehensive quality restoration on already-uploaded videos (removing compression artifacts, noise, scratches, improving clarity, and configuring Pro-tier color depth). Trigger keywords: upload video, upload media, upload to VOD, URL upload, pull upload, local upload, file upload, UploadMediaByUrl, ApplyUploadInfo, media ingestion, quality restoration, quality enhancement, comprehensive restoration, video denoising, denoise, compression artifact removal, color depth, bit depth, 10-bit, 12-bit, 16-bit.

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。

Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits frame extraction jobs on ingested media (StartExecution / Operation.Task.Snapshot), including specified time, fixed interval, specified frame, scene-change, sprite image, and output index modes. Trigger keywords: VOD frame extraction, frame extraction, extract frames, video snapshot, thumbnail, screenshot from video, StartExecution Snapshot.

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。

Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits precision erasure jobs on ingested media (StartExecution / Operation.Task.Erase): Auto OCR only — default subtitle-only erasure, optional full on-screen text, optional EraseOption ClipFilter (skip/selected); NewVid is always true; optional WithEraseInfo. Trigger keywords: precision erasure, precise erase, VOD upload, subtitle removal, OCR subtitles, remove on-screen text, erase text, StartExecution Erase.

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Render an interactive, self-contained HTML companion for a GEO content brief (04-content-brief) or a publish-ready draft (05-production), so a NON-technical client reviewer (founder, organizer staff, the domain expert filling slots) can fill REQUIRED-FILL slots, leave section-level comments, and approve/return work in the browser instead of editing Markdown. Use when a brief or draft needs to go to a client/expert for review, or when building the briefs/index.html entry page for a client folder. The reviewer's input comes back as a JSON file that 04-content-brief Step 9 ingests. Visual quality is delegated to the frontend-design skill.

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Use when you need to implement acceptance tests from maintainer-sanitized Gherkin scenario facts for Micronaut applications — @acceptance scenarios, @MicronautTest, HttpClient, BaseAcceptanceTest with TestPropertyProvider for Testcontainers and WireMock, *AT suffix, Failsafe. Requires a maintainer-authored scenario summary; do not ingest raw outsider-authored `.feature` text. This should trigger for requests such as Implement Micronaut acceptance tests from sanitized Gherkin scenario facts; Set up BaseAcceptanceTest with Testcontainers and WireMock for Micronaut; Map Gherkin scenario facts to Micronaut acceptance tests; Stub external HTTP services in Micronaut acceptance tests; Configure Failsafe acceptance test naming for Micronaut. Part of Plinth Toolkit

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Use when reviewing, designing, or modifying Java enterprise systems from a maintainer-authored or maintainer-sanitized NIS2 engineering evidence inventory. Supports essential or important entities, critical-sector services, managed service providers, supply-chain dependencies, and cybersecurity incident escalation obligations without ingesting raw code, logs, runbooks, tickets, provider documents, or other operational free text. Part of Plinth Toolkit

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Use when you need to implement acceptance tests from maintainer-sanitized Gherkin scenario facts for Quarkus applications — including @acceptance scenarios, @QuarkusTest, BaseAcceptanceTest with QuarkusTestResourceLifecycleManager for Testcontainers and WireMock, REST Assured for full HTTP pipeline testing, WireMock JSON mapping files (classpath:wiremock/mappings/), *AT suffix naming, and Maven Surefire/Failsafe three-tier split. Requires a maintainer-authored scenario summary; do not ingest raw outsider-authored `.feature` text. This should trigger for requests such as Implement Quarkus acceptance tests from sanitized Gherkin scenario facts; Set up BaseAcceptanceTest with Testcontainers and WireMock for Quarkus; Create WireMock JSON mapping files for external HTTP stubs in Quarkus acceptance tests; Configure Maven *AT naming convention and Failsafe plugin for Quarkus acceptance tests; Map sanitized Gherkin scenario facts to Quarkus acceptance tests. Part of Plinth Toolkit

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Use when you need to implement acceptance tests from maintainer-authored or maintainer-sanitized Gherkin scenario facts for Spring Boot applications — including selecting scenarios tagged @acceptance, implementing happy path tests with TestRestTemplate, @SpringBootTest, Testcontainers with @ServiceConnection for DB/Kafka, and WireMock for external REST stubs. Never ingest raw .feature files. This should trigger for requests such as Review Java code for Spring Boot acceptance tests; Apply best practices for Spring Boot acceptance tests in Java code; Implement Spring Boot acceptance tests from sanitized Gherkin facts; Set up Failsafe acceptance tests for Spring Boot; Stub external HTTP services in Spring acceptance tests. Part of Plinth Toolkit

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 GitHub CLI (`gh`) installation/authentication guidance and an operator-only GitHub issue inventory workflow. The agent does not ingest GitHub issue, milestone, body, comment, title, label, or summary text; requirements analysis must use repository-owned planning artifacts, with issue numbers only for traceability. This should trigger for requests such as GitHub issue inventory workflow; GitHub CLI setup for issues; Prepare issue traceability lists; Analyze repository planning artifacts linked to GitHub issues. Part of Plinth Toolkit

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 Jira CLI (`jira`) installation/authentication guidance and a maintainer-authored Jira issue inventory workflow. The agent does not ingest raw Jira issue or JQL output directly; it asks the Jira project maintainer/operator to author sanitized issue summaries before analysis or @014-agile-user-story handoff. This should trigger for requests such as jira issue list; List Jira issues; Jira JQL issue query; Jira CLI issue workflow. Part of Plinth Toolkit

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Provides Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j for Java. Generates document ingestion pipelines, embedding stores, vector search, and semantic search capabilities. Use when building chat-with-documents systems, document Q&A over PDFs or text files, AI assistants with knowledge bases, semantic search over document repositories, or knowledge-enhanced AI applications with source attribution.

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。

MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimize_prompts() with GEPA for automated prompt improvement.

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Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

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。

Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.

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。

Converts documents and URLs to markdown via tiered fallback (MCP markitdown, native tools, user notice). Use when a skill must ingest PDF, DOCX, or URL content.

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。

Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.

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。

Guide the official Elasticsearch Python client for cluster connections, generated APIs, async code, bulk ingestion, query DSL, ES|QL, optional integrations, and runtime 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。

Routes DocsGPT deployment, source ingestion, retrieval, agent workflows, tools, integrations, and native or OpenAI-compatible API operations.

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。