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SkillsMP는 xberg-io/plugins에서 56개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 56개 중 40개를 표시합니다.
Extract text, tables, metadata, and images from 98+ document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction…
원문 언어: 영어
Use when extracting a page needs scripted interaction first — click, type, press a key, scroll, wait, screenshot, or run JS before capturing the DOM. Covers `crawlberg interact URL --actions` with the real action schema, result shape, limits, and external-CDP…
원문 언어: 영어
Crawl, scrape, and convert websites to Markdown using the local crawlberg CLI and its MCP server. Use when the user wants to fetch a page, follow links across a domain, enumerate URLs, or drive a real browser. Covers installation, the subcommands (scrape,…
원문 언어: 영어
Use when the user wants to follow links across a domain and capture every reachable page as Markdown. Covers `crawlberg crawl` with depth, page caps, concurrency, rate limiting, domain scoping, robots, and output selection.
원문 언어: 영어
Use when a static fetch returns nothing useful and the page needs a real browser. Covers `--browser-mode auto|always|never`, external CDP via `--browser-endpoint`, symptoms of JS-only pages and WAF blocks, and the performance cost.
원문 언어: 영어
Use when the user wants the list of URLs on a site rather than the page content — sitemap analysis, link planning, or seeding another tool. Covers `crawlberg map URL` with `--limit`, `--search`, robots, output, and how it differs from a full crawl.
원문 언어: 영어
Use when the user wants a single page rendered as clean Markdown plus structured metadata. Covers `crawlberg scrape URL`, JSON vs Markdown output, what metadata is returned, and how to handle JS-heavy pages.
원문 언어: 영어
Use when the user wants a long-running HTTP service for scrape/crawl/map instead of one-shot CLI calls or the MCP server — for example wiring crawlberg into other apps over REST. Covers `crawlberg serve`, the Firecrawl-v1-compatible endpoints,…
원문 언어: 영어
Use when converting HTML to Markdown, Djot, or plain text. Covers output formats, heading and code-block styles, lists, escaping, wrapping, and HTML preprocessing.
원문 언어: 영어
Use when extracting metadata from HTML — title, description, language, Open Graph, JSON-LD / Microdata / RDFa, headers, links, and images. Covers the --json output shape and the --extract-metadata flag.
원문 언어: 영어
Use when extracting tabular data from HTML. Covers GFM Markdown tables, the structured tables array (grid cells plus pre-rendered markdown), and HTML line breaks in table cells.
원문 언어: 영어
Use when fetching a live URL and converting it to Markdown. Covers --url, custom user agents, preprocessing for noisy pages, and the --json ConversionResult shape.
원문 언어: 영어
Convert HTML to Markdown, Djot, or plain text with structured extraction. Use when writing code that calls html-to-markdown APIs in Rust, Python, TypeScript, Go, Ruby, PHP, Java, C#, Elixir, R, C, or WASM. Covers installation, conversion, configuration,…
원문 언어: 영어
Use when converting HTML to Markdown or extracting metadata and tables through the html-to-markdown MCP server's tools, rather than shelling out to the CLI. Covers the tool surface, the auto-installing launcher, and when MCP beats the CLI or SDK.
원문 언어: 영어
Use when sending chat completions through liter-llm and routing to a specific provider via the `provider/model` prefix. Covers the chat call shape, provider routing, model_hint, message roles, and error categories.
원문 언어: 영어
Use when generating embeddings, calling the 12 web-search providers, or running OCR over documents with the 4 OCR providers through liter-llm. Covers embed, search, and ocr methods plus reranking.
원문 언어: 영어
Universal LLM API client for 143 providers with native bindings for 14 languages. Use when writing code that calls LLM APIs via liter-llm in Python, TypeScript, Rust, Go, Java, C#, Ruby, PHP, Elixir, WASM, or C, when running the OpenAI-compatible proxy, or…
원문 언어: 영어
Use when running the `liter-llm api` OpenAI-compatible gateway — virtual keys, per-key rate limits, budgets, cost tracking, and model routing. Covers the TOML config and the 22 REST endpoints.
원문 언어: 영어
Use when streaming tokens incrementally from an LLM via liter-llm over SSE or async iterators. Covers chat_stream, delta handling, and null-content chunks.
원문 언어: 영어
Use when defining functions/tools for an LLM to call through liter-llm, or requesting structured JSON outputs. Covers tool schemas, tool_calls handling, and response formats.
원문 언어: 영어
Use when calling LLM APIs through the liter-llm MCP server's 22 tools, and to decide when MCP beats the CLI or SDK. Covers the tool surface, the auto-installing launcher, and authentication.
원문 언어: 영어
Use when the user wants to split source code into chunks for an LLM context window without breaking syntax mid-construct. Covers `ts-pack process --chunk-size`, why syntax-aware splits beat fixed-byte splits, picking a size, and the chunk JSON shape.
원문 언어: 영어
Use when the user wants to know which programming language a file or snippet is. Covers implicit detection in `ts-pack parse`/`process`, confirming support with `ts-pack list`/`info`, and the SDK detection functions for path, extension, and raw content.
원문 언어: 영어
Use when the user wants structured code metadata from a source file — functions, classes, imports, exports, symbols, docstrings, comments, or syntax diagnostics. Covers `ts-pack process` feature flags, the JSON result shape, and the default feature set.
원문 언어: 영어
Use when the user needs to manage the tree-sitter parser cache — prefetch parsers for offline or CI runs, list what is downloaded, inspect a language, find the cache directory, or clean it. Covers `ts-pack download`, `list`, `info`, `cache-dir`, `clean`, and…
원문 언어: 영어
Use when the user wants a tree-sitter syntax tree for a source file — an s-expression dump or JSON tree. Covers `ts-pack parse`, language auto-detection vs `--language`, stdin input, and reading `has_errors`.
원문 언어: 영어
Parse and extract code intelligence from 306 programming languages using tree-sitter grammars. Use when writing code that parses source, extracts structure/imports/exports/symbols/docstrings/comments, detects a language, runs syntax diagnostics, or produces…
원문 언어: 영어
Use when parsing source, extracting code structure, or detecting a language through the tree-sitter-language-pack MCP server's tools, rather than shelling out to the ts-pack CLI. Covers the tool surface, the auto-installing launcher, and when MCP beats the…
원문 언어: 영어
Use when extracting from many files at once with shared config, bounded parallelism, per-file overrides, and error recovery. Covers the `batch` command, `--file-configs`, `--max-concurrent`, and output layout.
원문 언어: 영어
Use when splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone `chunk` command.
원문 언어: 영어
Use when extracting keywords (YAKE/RAKE) from documents — and, secondarily, when detecting document language or generating embeddings for RAG and search. Covers the keyword config (and its feature gating), `--detect-language`, and the standalone `embed`…
원문 언어: 영어
Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.
원문 언어: 영어
Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
원문 언어: 영어
Use when choosing an output format for extracted documents — text, markdown, djot, html, or JSON. Maps consumer (LLM, parser, archive) to the right `--format` / `--content-format` pair.
원문 언어: 영어
Extract text, tables, metadata, and images from 91+ document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction…
원문 언어: 영어
Use when the user wants to follow links across a domain and capture every reachable page as Markdown. Covers `crawlberg crawl` with depth, page caps, concurrency, rate limiting, domain scoping, robots, and output selection.
원문 언어: 영어
Use when the user wants a single page rendered as clean Markdown plus structured metadata. Covers `crawlberg scrape URL`, JSON vs Markdown output, what metadata is returned, and how to handle JS-heavy pages.
원문 언어: 영어
Use when converting HTML to Markdown, Djot, or plain text. Covers output formats, heading and code-block styles, lists, escaping, wrapping, and HTML preprocessing.
원문 언어: 영어
Use when extracting metadata from HTML — title, description, language, Open Graph, JSON-LD / Microdata / RDFa, headers, links, and images. Covers the --json output shape and the --extract-metadata flag.
원문 언어: 영어
Use when extracting tabular data from HTML. Covers GFM Markdown tables, the structured tables array (grid cells plus pre-rendered markdown), and HTML line breaks in table cells.
원문 언어: 영어