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Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.

Convert one PDF bank statement through the complete MainBook workflow: create a job, upload, start, poll, and return structured data. This creates a job and spends page credits; it is not read-only.

Return total, reserved, and available MainBook credits. Every value is measured in PDF pages.

Saves an email to the Mail.app Drafts folder for the user to review and send manually — it never sends. Compose a new draft with `to`/`subject` and `body` or `html_body`, or save a native reply with `reply_to_message_id`, `reply_all`, and `body` or `html_body`; the response names the Drafts mailbox and subject. A reply draft's response includes `threaded`: true means the saved draft was read back and its headers reference the source message (it will appear inside the conversation); false means it saved WITHOUT threading headers (relay the warning to the user); "unconfirmed" means it could not be read back in time (e.g. Exchange sync lag). On a multi-account Mac, pass `account` (an account name from list_email_accounts) or `from` (a sender address) to place the draft in that account's Drafts; otherwise it lands in the default account. Attach files by passing `attachments` (comma-separated absolute file paths, e.g. a PDF quote) — they are attached to the saved draft. Use this for the cautious user who wants AI-composed mail but insists on sending it themselves. Requires confirm=true to actually save it — without it, returns a preview without touching Mail.app.

Reads a plain text file from the local filesystem by its absolute path — the primary, default tool for reading a local text file (use this unless the file is a PDF, Word, Excel, or PowerPoint document, which have their own readers). The path must be inside an allowed folder — the same allowlist as file_write (the home directory by default; extend via Settings → Advanced → Allowed folders). A path outside the allowlist returns an actionable 'access denied' naming the allowed folders. Supports .txt, .md, .csv, .json, .xml, .log, .yaml, .toml and common code file types; auto-detects UTF-8 with Latin-1/Windows-1252 fallback. For files in OneDrive use onedrive_read_file, in Google Drive gdrive_read_file; for PDFs pdf_read, Word word_read, Excel excel_read.

Reads a text file from the synced Google Drive folder (.txt, .md, .csv, .json, code files...). Note: native Google Docs/Sheets/Slides sync as .gdoc/.gsheet pointers, not real files — export them from Drive or read Office/PDF copies instead. Auto-detects UTF-8 with Latin-1/CP1252 fallback. For files outside Google Drive, use file_read.

Reads and extracts text from a PDF document (.pdf file).

Stamp page numbers or footer text onto every page of a PDF. Supports a starting number, roman numerals, skipping a cover page, position and font size — the combination Acrobat cannot do without scripting. Template supports {n} and {total}, e.g. "Page {n} of {total}".

Markdown → styled PDF. Send markdown text or a URL to a .md file, get a print-ready PDF back.

Merge several PDFs (by URL) into one. urls = comma-separated links, in order.

Extract a page range from a PDF (by URL) into a new PDF. from/to are 1-based page numbers.

Count pages and report each page size of a PDF (by URL).

Stamp diagonal text watermark on every page of a PDF (by URL). text = the watermark.

Convert a transaction CSV into a .qbo / OFX bank-feed file that QuickBooks and similar accounting software import directly. Needs date, description and amount columns (or debit + credit). Pairs with extract_statement: statement PDF in, importable bank feed out.

Check a resume (PDF or .docx) the way an applicant tracking system reads it: is the text extractable, are email/phone/sections findable, do multi-column layouts, tables or emoji break parsing. Returns a score plus concrete fixes ordered by impact — like the W3C validator, but for resumes.

Convert a PDF (or a scanned page image) into clean Markdown that keeps headings, lists and tables, and puts multi-column pages in the right reading order. Text-layer PDFs are read exactly and cost far less; images go through a vision model.

Extract tables from a PDF into structured rows (JSON + CSV). Pass fields to force a fixed set of columns — that aligns a pile of documents that each name their headers differently into one consistent table. Rows the model was unsure about are flagged rather than guessed. Text-layer PDFs only.

Turn a bank statement or transaction PDF into a clean transaction table (JSON + CSV), then cross-check it: opening + credits - debits must equal the stated closing balance. If it does not balance you get the exact difference and which row the running balance first breaks at — so you know whether the table is safe to use for accounting. Text-layer PDFs only (scanned images not yet supported).

Give it up to 20 invoice URLs (PDF or page images) and get back one table ready to post: number, date, seller, buyer, net / tax / gross, currency. Every row is checked in code — net + tax must equal gross — and the batch total is re-added independently, so a row the model misread is flagged with the exact difference instead of quietly landing in your books. Mixed currencies get no batch total on purpose: adding them together would be an accounting error. CSV is UTF-8 with BOM so Excel opens it right.

Attach a supporting text document to a calendar — a syllabus/curriculum, exam spec, training history, race info. Stored with the calendar so any future session can read it when revising the plan. Text only (paste text out of PDFs), max 5 docs × 200KB.

Generate a PDF or Excel document from HTML (document_content) or a URL (document_url). Exactly one of document_content / document_url is required. By default the document is HOSTED and the tool returns a { download_url } you can fetch — ideal for agents (no large binary in the response). Set hosted:false to get the raw document back as base64, or async:true to enqueue a job and poll docraptor_get_document_status. IMPORTANT: real documents consume account credits (billed). Set test:true to generate a FREE, watermarked document while developing. DocRaptor API: POST /docs.

Look up the manufacturer safety data sheet (SDS/MSDS) for a workplace chemical or product by name. Returns the product name, manufacturer, CAS number(s), EPA registration where applicable, a link to the actual SDS PDF, and a confidence level. If the product cannot be identified reliably it says so plainly rather than guessing — a wrong SDS is worse than none. Free, no signup. Use it when someone needs hazard or handling information, or the SDS, for a chemical they keep on site.

Add a file to a task or remove one. `action: "add"` fetches the given HTTPS `url`: the server downloads it, verifies its size and type, and stores it, so the model never sends file bytes. Pass a stable idempotency_key and reuse it for retries so a lost response cannot upload the file twice. `action: "remove"` deletes the named `attachment`. Read a task's files with task_show and `include: ["attachments"]`. Limited to 10 attachments per task and 10 MB per file. Allowed types: images (jpeg, png, gif, webp, heic), PDF, CSV, Markdown, and plain text.

把 PDF / Word(.docx) / PPT(.pptx) / HTML / 纯文本 解析成干净 Markdown + 结构化（按实际解析页数计费，每页 1 credit）。 纯解析 + 格式转换、不生成任何 AI 内容；扫描件 OCR 暂未支持。 支持 page_range 只解析指定页码段（只按解析的页数扣费）。

抽取文档中的表格（PDF / .docx / .pptx），转成 headers+rows 的 JSON 可直接计算。 与 doc_parse 的区别：表格不再压平成 markdown 竖线文本，而是结构化行列， AI 可直接算合计/对比；PDF 用版面识别找表格。

抽取文档内嵌的图片（PDF / .docx / .pptx），打包 ZIP 落文件中转站并返下载 URL。 过滤 <1KB 的图标噪声；多模态 AI 可配合 doc_parse 的文本一起理解图文文档。

Step 4 of the Tango working agreement (work in the open). Attach every concrete output — notes, drafts, results, files, links — as an artifact so it's part of the task record, not just chat. Real files (pdf, docx, pptx, xlsx, mp3, wav, m4a, images…) are supported: pass `content_base64` for files up to ~6 MB, `fetch_url` to have Tango download and store a hosted file itself, or call create_artifact_upload first for large files and finalize here with `upload_token`. `content` stays the path for inline text and `external_url` for a link you only want recorded. Reference artifact ids in complete_task's evidence_artifact_ids. If a lease is active, Tango attributes the artifact to the lease holder. Otherwise, pass `acting_worker_id` to identify which of your workers is acting; if you don't own that worker the attribution is dropped rather than misrecorded. Attested workers may pass `worker_signature` over the JCS-canonical artifact payload (type 'tango.artifact'); an invalid signature rejects the call and nothing is stored. Delegated workers are signed for automatically.

Use this when you need to attach a file too big for add_artifact's inline base64 path (~6 MB): decks, PDFs, audio recordings, archives. Returns a short-lived signed upload URL plus an upload_token. PUT the raw file bytes to upload_url (Content-Type set to the file's type, no base64), then call add_artifact with the same task_id, name and upload_token to record the artifact. Nothing is recorded until you finalize, so an abandoned upload leaves no artifact behind.

Extract a PDF into clean Markdown and structured elements (headings, paragraphs). Returns the canonical ExtractedDocument object. mode "hybrid" runs a heavier semantic engine that also reconstructs tables and bounding boxes; the default "fast" engine is prose-only (low confidence.tables).

Split a PDF into semantic chunks ready for embeddings (RAG). Each chunk carries its text, estimated tokens, starting page, section heading and the source element ids for citation.

Return every table in a PDF as structured JSON (reconstructed rows and columns) with page and bounding box for verifiable citations. Uses the semantic (hybrid) engine.

Publish a PDF as a tracked doc.page Doc Link and get back a shareable URL. The link belongs to the API key's account and also appears in its doc.page library. Requires an API key. Free plan: up to 3 active links; custom vanity slugs are premium-only. Optional expiry and open-notification toggle.

把 Markdown 渲染成 PDF 文件，存进你的文件中转站并返回下载 URL（2 credit/次）。 纯本地渲染（markdown + weasyprint），中文正常显示；不生成任何 AI 内容。失败自动退款。

Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.