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Return verbatim text from the Federal Council Botschaft (or Erläuterungsbericht) explaining the legislative purpose of a specific article. Joins the verbatim Botschaft corpus (post-2003 BBl publications, Akoma Ntoso XML where available, PDF fallback otherwise) with the article-Botschaft link table. Returns one entry per source — original Botschaft + any amendment Botschaften. All paragraphs are verbatim text the LLM can quote with `bbl_citation, S. {page}` references. USE THIS when the user asks 'what was the purpose of Art. X' or 'what did Parliament intend' or 'why does Art. X exist'. Coverage is rolling — empty `sources` means the verbatim corpus hasn't ingested that article's Botschaft yet; fall back to get_doctrine for the digest layer.

AUTHORITATIVE LOOKUP for the text of any Swiss law article — federal OR cantonal — from two local mirrors. Federal (canton='CH', default): Fedlex mirror, all federal acts (OR, ZGB, StGB, StPO, ZPO, BV, SchKG, BGG/LTF, DBG, IPRG, AIG, BVG, KVG, AsylG, BGFA …) in DE/FR/IT. Cantonal: LexFind mirror, every statute and ordinance of all 26 cantons in the canton's language. Same shape for both (title, articles with heading + text, article_count, canton, level). Use this BEFORE relying on training-data recall — statute text changes often and LLMs hallucinate article content. With as_of: the dated Fedlex edition in force on that date (snapshot_date, title, in-force window, link); always tell the user the edition date. PDF-only editions carry `text_status`: 'heading_only' / 'empty' = no article text recovered; say so and give the Fedlex link. Examples: get_law(abbreviation='BV', article='8'); get_law(sr_number='220', article='41'); get_law(canton='ZH', sr_number='554.5', article='1').

Retrieve the FULL TEXT and article list of a specific Swiss law, federal or cantonal, by LexFind ID or SR/systematic number. For federal laws in the Fedlex mirror this is instant (local SQLite). For cantonal laws, the law is downloaded from LexFind as PDF, parsed with PyMuPDF, and segmented into articles (cached 30 days). Returns: title, entity, articles (article_num, heading, text), full_text, article_count. Use search_legislation first to find the right lexfind_id or systematic_number; then pass it here. For the core federal codes, get_law is still the fastest path.

Use this tool when the question involves federal ADMINISTRATIVE PRACTICE (Verwaltungspraxis): Wegleitungen, Kreisschreiben, Weisungen, Rundschreiben — agency guidance, not court decisions. 9,900+ documents. Covered: BSV (AHV/IV/EL/EO/FamZ/BVG Wegleitungen, Kreisschreiben, Mitteilungen, every version), OAK BV (BVG Weisungen, Mitteilungen, drafts), WEKO (Bekanntmachungen, Erläuterungen, all versions), SECO (ArG commentary, AVIG-Praxis), BAG (KVG Kreisschreiben), SEM (Weisungen AIG/Asyl/BüG, Handbuch Asyl), BJ (SchKG Weisungen, Existenzminimum), FINMA, ESTV, BAFU; counts in the filter enums. Returns ranked excerpts with authority, number, date, PDF link. Superseded versions collapse to the newest per document; for past conduct pass include_superseded=true and take the version dated before the facts. NOT covered: cantonal administrations — Sozialhilfe (SKOS, cantonal Handbücher), Prämienverbilligung (IPV) — say so, do not imply absence of guidance. Pre-2017 federal decisions: search_decisions(court='ch_vb').

Retrieve a single federal administrative-practice document by its doc_id (e.g. 'estv_ks_ks_nr_28', 'sem_weisungen_weisungen-aug-d', 'bsv_weisungen_6930_v20_de', 'seco_alv_avig_ale_de'). Returns full body text, title, date, issuing authority, and PDF URL. Use search_practice first to discover the doc_id.

Translate a document into another language with the original layout and formatting preserved (DOCX, PPTX, XLSX, PDF, TXT, MD, SRT, VTT). The job runs immediately and returns a FREE preview of the first pages plus a secure Stripe checkout link — the full translated file unlocks after payment ($4.99, one-time, no account needed). Provide EITHER source_url OR base64_content, plus a filename with extension.

Extract every table from a PDF or image (PNG, JPG, WebP) into a clean multi-sheet Excel file. The job runs immediately and returns a FREE preview of the first table plus a secure Stripe checkout link — the full .xlsx unlocks after payment ($3.99, one-time, no account needed). Provide EITHER source_url OR base64_content, plus a filename with extension.

Compress a file (PDF, JPG, PNG, WebP, MP4, MOV, WebM) down to an exact target size — e.g. "under 5MB for an upload form". FREE (daily limit applies). Returns a download URL on success; if the target is physically unreachable it fails honestly and reports the smallest achievable size. Provide EITHER source_url OR base64_content, plus a filename with extension.

Describe what you want done to a file in plain language — e.g. "translate this contract to German", "pull every table out of this PDF into Excel", "shrink this video to under 25MB", "convert this to PDF". The instruction is routed to the right job automatically; if the request is not supported yet you get an honest explanation of what is. Provide EITHER source_url OR base64_content, plus a filename with extension.

Upload assets for PowerPoint (.pptx) generation: company template, logo, image, or document — or AI-generate an image. Purposes: • logo — company logo for chrome (PNG/JPG/SVG, max 5MB) → logo_id • image — image for the Image component (max 10MB) → asset_id • theme — company template PPTX → theme_id; slides with it render NATIVELY on the template (masters/layouts/chrome) • generate_image — AI-generate via `prompt` → asset_id ($0.05) • translate — PPTX to translate → deck job_id ($0.02/slide; requires `target_language`) • pdf — PDF → editable slides; pass `target_language` to also translate • recreate — image OF a slide → editable PPTX slide ($0.10; honest annotate/preserve fallback, refusals free). Use `image` to just place a picture Files >3MB (pdf/translate/theme) — and recreate on chat hosts — omit `data`: a drop-zone appears in the result card; bytes never pass through the agent.

Use when a user has ONE specific lat/lon (a parcel, a candidate site) and wants the full multi-factor data-center suitability read in one call. Example: "Score this Phoenix parcel for a 100MW build — power, gas, fiber, market & risk." — analyze_site lat=33.45 lon=-112.07 capacity_mw=100 state=AZ. Params: lat (-90 to 90, required unless candidate_id or location), lon (-180 to 180, required unless candidate_id or location), location (a market NAME or metro slug instead of coordinates, e.g. location="ashburn" — resolved to that market's PUBLISHED CENTROID through the DCPI market row, with a resolved_from block naming what it resolved to; a MARKET-level read, NOT the parcel you named, and a trailing state is not stripped so "Ashburn, VA" will not resolve), candidate_id (a cand_… from get_refined_queue — resolves coordinates from the frozen mint and ignores lat/lon), capacity_mw (target load in MW, e.g. 50-500 — returns a `capacity_context` block sizing that load against nearby installed generation; it deliberately does NOT move overall_score, and the block names where the load IS applied), state (2-letter US, optional — improves the tax-incentive/context lookup), include_grid/include_risk/include_fiber (booleans, default true). Returns (full, paid): {overall_score (aka composite_score, 0-100 composite — for the integrity-first version that never imputes a missing factor, use get_composite_site_score), interpretation (verdict string, e.g. "Excellent site"), scores{power_infrastructure, gas_pipeline_access, fiber_connectivity, market_conditions, risk_resilience — each 0-100}, nearby{substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw}, power_cost{industrial_cents_kwh, commercial_cents_kwh, period, basis}, fiber{connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk}, location, citation}. FREE tier returns a REAL, citable HEADLINE — composite_score + verdict + the single top limiting factor (the lowest sub-score) + citation; the full per-factor breakdown, nearby infrastructure, power cost, fiber carriers, and the branded Site Analysis PDF (generate_site_analysis) are Pro. For dedicated water / disaster / climate / tax reads use get_water_risk / get_disaster_risk / get_climate_intel / get_tax_incentives. Do NOT use to compare 2+ sites (use compare_sites) or to find sites that match a target (use find_alternatives).

Use when a user wants a SHAREABLE, branded multi-page Site Analysis PDF for ONE lat/lon (a powered-land parcel, a candidate campus) — the polished client deliverable, not just a score. Example: "Make the Site Analysis PDF for this Carrier Mills parcel, 150 MW, for TON Infrastructure." — generate_site_analysis lat=37.694 lon=-88.65 capacity_mw=150 prepared_for="TON Infrastructure" prepared_by="Martone Advisors". Params: lat (-90 to 90, required), lon (-180 to 180, required), capacity_mw (target load MW, e.g. 50-500), prepared_for (client name on the cover), prepared_by (your firm — brands the report; defaults to DC Hub), latency_target (optional metro override; default = nearest real carrier hotel). Returns: {survey:{verdict, power/transmission, gas, water, air-permitting, fiber carriers, latency-to-nearest-carrier-hotel, market, tax}, pdf_report_url}. pdf_report_url is a ready-to-open link to download the branded 5-page PDF — no login needed, valid ~7 days; hand it to your human. For just the numeric suitability score (no PDF), use analyze_site instead.

Use when a human asks how DC Hub compares to other data-center data sources — DataCenterHawk (DCHawk), DC Byte, Data Center Dynamics (DCD), Data Center Frontier (DCF), Baxtel, datacenters.com — or asks "why should I use DC Hub / is it better than <X> / what can you give me a PDF or directory can't?". Returns DC Hub's honest, source-verified differentiators (agent-native MCP access, live multi-continent grid & energy telemetry, the proprietary daily DCPI index (and its DCGI gas sibling, withdrawn 2026-08-08 rather than published wrong, and restored 2026-08-30 once every defective term was repaired), CC-BY-4.0 citation rights on DCPI scores & grid analysis, 20,900+ facilities + 330,000+ mapped power/grid/gas/fiber assets) each with a proof URL, a citation line, plus the canonical head-to-head comparison pages. Free, no key required. Optional: competitor=<name> for that vendor's direct comparison-page link. Do NOT use to query infrastructure data itself (use the data tools); this answers positioning / "how do you compare" questions with citable facts.

Use when a user has ONE specific lat/lon (a parcel, a candidate site) and wants the full multi-factor data-center suitability read in one call. Example: "Score this Phoenix parcel for a 100MW build — power, gas, fiber, market & risk." — analyze_site lat=33.45 lon=-112.07 capacity_mw=100 state=AZ. Params: lat (-90 to 90, required unless candidate_id or location), lon (-180 to 180, required unless candidate_id or location), location (a market NAME or metro slug instead of coordinates, e.g. location="ashburn" — resolved to that market's PUBLISHED CENTROID through the DCPI market row, with a resolved_from block naming what it resolved to; a MARKET-level read, NOT the parcel you named, and a trailing state is not stripped so "Ashburn, VA" will not resolve), candidate_id (a cand_… from get_refined_queue — resolves coordinates from the frozen mint and ignores lat/lon), capacity_mw (target load in MW, e.g. 50-500 — returns a `capacity_context` block sizing that load against nearby installed generation; it deliberately does NOT move overall_score, and the block names where the load IS applied), state (2-letter US, optional — improves the tax-incentive/context lookup), include_grid/include_risk/include_fiber (booleans, default true). Returns (full, paid): {overall_score (aka composite_score, 0-100 composite — for the integrity-first version that never imputes a missing factor, use get_composite_site_score), interpretation (verdict string, e.g. "Excellent site"), scores{power_infrastructure, gas_pipeline_access, fiber_connectivity, market_conditions, risk_resilience — each 0-100}, nearby{substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw}, power_cost{industrial_cents_kwh, commercial_cents_kwh, period, basis}, fiber{connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk}, location, citation}. FREE tier returns a REAL, citable HEADLINE — composite_score + verdict + the single top limiting factor (the lowest sub-score) + citation; the full per-factor breakdown, nearby infrastructure, power cost, fiber carriers, and the branded Site Analysis PDF (generate_site_analysis) are Pro. For dedicated water / disaster / climate / tax reads use get_water_risk / get_disaster_risk / get_climate_intel / get_tax_incentives. Do NOT use to compare 2+ sites (use compare_sites) or to find sites that match a target (use find_alternatives).

Use when a user wants a SHAREABLE, branded multi-page Site Analysis PDF for ONE lat/lon (a powered-land parcel, a candidate campus) — the polished client deliverable, not just a score. Example: "Make the Site Analysis PDF for this Carrier Mills parcel, 150 MW, for TON Infrastructure." — generate_site_analysis lat=37.694 lon=-88.65 capacity_mw=150 prepared_for="TON Infrastructure" prepared_by="Martone Advisors". Params: lat (-90 to 90, required), lon (-180 to 180, required), capacity_mw (target load MW, e.g. 50-500), prepared_for (client name on the cover), prepared_by (your firm — brands the report; defaults to DC Hub), latency_target (optional metro override; default = nearest real carrier hotel). Returns: {survey:{verdict, power/transmission, gas, water, air-permitting, fiber carriers, latency-to-nearest-carrier-hotel, market, tax}, pdf_report_url}. pdf_report_url is a ready-to-open link to download the branded 5-page PDF — no login needed, valid ~7 days; hand it to your human. For just the numeric suitability score (no PDF), use analyze_site instead.

Use when a human asks how DC Hub compares to other data-center data sources — DataCenterHawk (DCHawk), DC Byte, Data Center Dynamics (DCD), Data Center Frontier (DCF), Baxtel, datacenters.com — or asks "why should I use DC Hub / is it better than <X> / what can you give me a PDF or directory can't?". Returns DC Hub's honest, source-verified differentiators (agent-native MCP access, live multi-continent grid & energy telemetry, the proprietary daily DCPI index (and its DCGI gas sibling, withdrawn 2026-08-08 rather than published wrong, and restored 2026-08-30 once every defective term was repaired), CC-BY-4.0 citation rights on DCPI scores & grid analysis, 20,900+ facilities + 330,000+ mapped power/grid/gas/fiber assets) each with a proof URL, a citation line, plus the canonical head-to-head comparison pages. Free, no key required. Optional: competitor=<name> for that vendor's direct comparison-page link. Do NOT use to query infrastructure data itself (use the data tools); this answers positioning / "how do you compare" questions with citable facts.

Estimate the permit fee for a residential project based on jurisdiction, project type, and project valuation. Returns numeric breakdown when the authoritative rule has fee inputs, or qualitative feeNotes (with source URL) when the city publishes fees only as PDFs/spreadsheets. Never fabricates dollar amounts.

Fetch the full body of a published report by slug. Returns the report's structured fields plus content_html (the canonical body). For a PDF, use pdf_url when present, or append .pdf to the URL.

Attach a document to a case (invoice copy, contract, correspondence, proof of delivery). Max 25 MB. Allowed extensions: .pdf, .xls, .xlsx, .csv, .txt, .jpg, .jpeg, .png, .gif. Provide the file content base64-encoded.

입주자모집공고문 원문을 쪽 단위로 읽는다 — 팩트시트에 없는 세부(특별공급 소득·자산 기준, 부적격 처리, 계약 유의사항, 옵션 품목 상세)는 이 도구로 원문을 직접 확인하라. 표가 있는 쪽은 pdftotext 특성상 정렬이 깨질 수 있다 — 열 해석이 애매하면 단정하지 말 것. 여러 낱말은 AND로 묶인다('가점제 추첨제'→둘 다 있는 쪽). 0쪽이면 막다르지 않고 낱말별 히트 쪽과 부분일치 상위 쪽을 함께 돌려주니 그걸로 좁혀라(match='any'로 넓힐 수도 있다). **쪽을 모를 땐 pages_only=true로 먼저 훑어라** — 전문은 한 번에 수만 자다. 전문 응답은 최대 6쪽이고, meta.matching_pages에 일치 쪽 전체 목록이 늘 들어 있다.

Converts an accepted proforma of this company into a real invoice. The new invoice is created as a `STANDARD` draft linked back through `source_proforma_id`. - **What converts:** only proformas in status `ACTIVE`. One shown as `EXPIRED` is still `ACTIVE` underneath and converts too. - **The proforma:** preserved as the record of what the customer accepted — it keeps its `PRO-...` number and PDF and moves to the terminal status `CONVERTED`. - **`issue`:** with `true` the new invoice is numbered and issued in the same atomic call. If issuing fails nothing is created and the proforma stays `ACTIVE`. - **Errors:** `422 CONVERSION_REQUIRES_PROFORMA` when the document is not a proforma, `422 PROFORMA_NOT_CONVERTIBLE` when it is not `ACTIVE`, and `409 PROFORMA_ALREADY_CONVERTED` when it has already been converted — a second call never creates a second invoice. Endpoint: POST /v1/companies/{company_id}/invoices/{invoice_id}/convert-to-invoice ⚠️ Fiscal guardrails — read before calling: - When an invoice can still be changed, and what to do once it cannot. (resource: beel://guardrails/invoice-state-machine) For the exhaustive rules and worked examples, call beel_docs_search.

Applies one operation to a set of invoices of this company and reports, invoice by invoice, which succeeded and which failed. - **Operations:** `ISSUE` issues the draft invoices; `STATUS` moves them to the `new_status` given in the body. - **Limit:** up to 50 invoices per request (`invoice_ids`). - **Not atomic:** each invoice is processed on its own, and since issuing is irreversible, the ones already issued stay issued if a later one fails. - **Related:** downloading PDFs, sending email and exporting are not operations of this batch — use `…/invoices/pdf-archive`, `…/invoices/deliveries` and `…/invoices/exports`. Endpoint: POST /v1/companies/{company_id}/invoices/batches

Sends one email carrying the PDFs of several invoices of this company as attachments. - **`recipients`:** required, and must carry at least one address; no address is inferred from any profile. - **Limit:** up to 200 invoices per message (`invoice_ids`). - **Failures:** invoices whose PDF cannot be attached are reported in `failures`, and the message is still sent with the rest. Endpoint: POST /v1/companies/{company_id}/invoices/deliveries

Creates a draft invoice derived from an existing invoice of this company. The source invoice, named in `from_invoice_id`, is not modified. - **`mode`:** the only value is `DUPLICATE`, which copies the source into a fresh draft. Recipient, lines, payment method, series and observations are copied; number, status, dates, VeriFactu data and PDF are reset. - **Series:** the one sent in `series_id`, or the source's when omitted. It is validated against the type of the copy, which is not always the source's: the copy of a `CORRECTIVE` is born `STANDARD`. An incompatible series fails with `422 SERIES_INCOMPATIBLE_DOC_TYPE`. Endpoint: POST /v1/companies/{company_id}/invoices/derivations ⚠️ Fiscal guardrails — read before calling: - When an invoice can still be changed, and what to do once it cannot. (resource: beel://guardrails/invoice-state-machine) For the exhaustive rules and worked examples, call beel_docs_search.

Returns a presigned URL, valid for 5 minutes, to download the representation PDF of a company. - **Which copy:** while the document is unsigned it serves the generated one; once the signed copy has been submitted it serves that. - **Not generated yet:** a company that has not generated the document is rejected with `400`. Endpoint: GET /v1/companies/{company_id}/representation/document

Generates the unsigned AEAT representation PDF of a company, the first step of the representation flow. - **Next steps:** download the PDF from `GET /v1/companies/{company_id}/representation/document`, sign it digitally and return it through `POST /v1/companies/{company_id}/representation/submit`. - **Fiscal identity:** must be complete before the document can be produced. An incomplete one is rejected with `400` naming what is missing. - **Existing representation:** a company that already holds an active one is rejected too. Cancel it first. Endpoint: POST /v1/companies/{company_id}/representation

Generate the shipping label PDF for one or more orders. REQUIRES the FULL pipe-suffixed order ids (order-xxx|123) — stripped ids are rejected upstream. Returns a temporary URL (valid ~10 minutes) where the PDF can be downloaded.

Get a focused reading for ONE specific divination system from the 26. Free MCP tier covers the 5 preview systems (bazi, vedic, western, ninestar, thai); the other 21 + the in-depth Cosmic Blueprint PDF are at mythsensus.com/pricing.

一批 URL 的中国大陆可达性体检 → PDF 报告:逐个的可达结论、延迟、HTTP 状态与大陆 DNS 解析到的 IP。探测从真实的中国移动骨干网节点发出,不是境外 VPS 推断。入参 urls(数组或逗号分隔,最多 20 个)。自证不通过不计费。

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.

Compose a grounded report plan, optionally preview without spending export meter (`preview=true`), or confirm export (`confirm=true`) to save the plan and return a short-lived signed download URL plus a receipt — never PDF bytes in the tool result. Confirm spends `records.exports` and is irreversible.

Start a promotional Appraisily Lotbook run whose finished PDF includes the Appraisily logo. Use this for marketing, demos, social posts, or other public Appraisily-branded leave-behinds. Do not use this for a client/white-label packet; that is start_pro_screener_run, which stays unbranded. No Appraisily login is required. Provide a public HTTPS photo. Optional notes help the research. Returns a sessionId immediately; poll get_pro_screener_status, then get_pro_screener_pdf for a public assets.appraisily.com/promotional-lotbook URL. The submitted photo and finished PDF are public marketing artifacts owned by Appraisily.

Return the Lotbook PDF URL once the report is ready. Promotional runs return a durable public assets.appraisily.com/promotional-lotbook URL. No login is required for those sessions. Private client packets still use a short-lived signed URL. Never publish customer PDFs to /appraisals or /sessions.

[Results] Generate an interview result report (HTML/PDF/JSON) for a completed interview. The report is decision-support material for a human reviewer, not an automated hiring decision. Generates an interview result report as a PDF (returns a signed URL), raw HTML, or structured JSON. Provide either `interview_result_id` for a single result or `interview_result_ids` for a combined multi-result report.

Pricing and checkout links for the Blue Crane Form Maker Pass: one-time purchase that strips all Blue Crane text from printed PDFs (clean, client-ready paper) and auto-fills saved company details across all 126 forms.

Estimate the PROBABILITY that a document's text was AI-GENERATED (LLM-written prose). USE THIS WHEN someone shares prose — an essay, cover letter, article, review, application, or report (or a link to one) — and asks: did an AI / ChatGPT write this? is this human-written? detect AI text. Provide the document ONE way: `text` (pasted markdown/plain prose), `url` (a public http(s) link to a page or PDF — fetched server-side, the cheapest call), OR `bytes_b64` (a base64 PDF/file, plus `filename` for routing). Returns `{probability, lean, tells, reasoning, applicable}`. HONEST SCOPE: the probability is the model's CONFIDENCE, not a calibrated truth — it can false-flag templated/coached or non-native-English writing. It works on PROSE only: for a form/table/numeric document (payslip, statement) it returns `applicable: false` and abstains, because AI-text detection false-positives badly there — use `verify_document` (the authenticity engine) for those, and `verify_references` to check a doc's citations/claims.

Fact-check a document's REFERENCES and CLAIMS — built for AI-generated reports whose citations must be checked before they're trusted. USE THIS WHEN someone shares a report, article, whitepaper, or deep-research export (or a link to one) and asks: is this accurate / legit? are these citations real? fact-check this. did the AI make this up? Also use it proactively before relying on any AI-written document. Provide the document ONE way: `url` (a public http(s) link to a PDF or web page — fetched server-side, the cheapest call: no need to download or encode anything), `text` (pasted markdown/plain prose), OR `bytes_b64` (a base64 PDF; URLs are read from the PDF's link annotations, so they're exact). Default (fast): provenance (is it a ChatGPT deep-research export?), citation resolution (live / archived / dead, papers matched against arXiv/Crossref to catch 'real ID, wrong paper'), and internal MATH (recompute the doc's own arithmetic). Set `deep=true` to also fetch each cited source and judge whether it SUPPORTS or CONTRADICTS the claim (slower, ~a minute). Returns a trust summary, per-item tables, and a shareable `permalink` to the public fact-check record. HONEST BOUNDARY: this reports verification COVERAGE, not truth — 'supported' means evidence-backed (not necessarily true) and 'unsupported' means no evidence found (not necessarily false). It tells a reviewer WHERE to look; it does not bless the document, and it never affects the fraud risk band.

Order a formatted, downloadable financial report (Excel or PDF) for a Norwegian company — the same multi-source-fused figures, layout and source note as the report a customer would download in the Firmaradar portal, ready to file or forward. Returns a short-lived download link + metadata (years covered, source, currency), NOT the file itself and NOT base64 data — fetch the download_url separately, no further auth required, within expires_in seconds. Use `get_company_financials` instead when you need the raw figures to reason about, not a document to hand off. Requires the Excel-export or PDF-export add-on (matching the requested format) on the caller's account. Charges 1 credit per financial year included in the report.

Fetch a single invoice by id (full object incl. items, taxes, payments, permalink, pdf). Quaderno API: GET /invoices/{id}.

MUTATES Quaderno data — create an invoice for a contact. Provide contact_id (or a contact via `fields`) and items; use `fields` for any other attribute (currency, issue_date, due_date, po_number, notes, tag_list, custom_metadata, payment_details). Each item = { description, quantity, unit_price, tax_1_name?, tax_1_rate?, discount_rate?, … }. Quaderno API: POST /invoices. Returns the created invoice (incl. permalink, pdf).

Download links for the printable PDF. pdf_url is the merged tournament document (match sheet with write-in score boxes, player sheet, standings/results when they exist) — hand this to the organiser. results_pdf_url and plan_pdf_url are deprecated pre-merge variants kept for comparison.

The printable PDF itself, returned as a base64 embedded resource — use this when the organiser wants the file handed to them and your client cannot fetch URLs. Default "sheet": the merged tournament document (match sheet with write-in score boxes, player sheet, standings/results when they exist). "results" and "plan" are deprecated pre-merge variants kept for comparison. For a lighter response, get_pdf_link returns download URLs instead.

查立法院開放資料平台（data.ly.gov.tw 官方直連）取得法律的立法歷程：該法所有修法提案的提案人、連署人、議案狀態與官方關係文書（PDF/DOC）連結。補「修法沿革」上游的立法過程（誰提案、審到哪裡）。資料授權：政府資料開放授權條款第 1 版（與 CC-BY-4.0 相容）。

查立法院開放資料平台（官方直連）取得法律的三讀通過紀錄與附帶決議：三讀屆會次、三讀通過條文 PDF、附帶決議內容。涵蓋近年（2023 起）三讀紀錄；完整修正沿革請併用 search_taiwan_laws 查全國法規資料庫。資料授權：政府資料開放授權條款第 1 版。

搜尋立法院議案提案（官方直連 data.ly.gov.tw）：以提案名稱關鍵字、提案人、屆期、議案狀態查詢。回傳議案編號、名稱、提案單位、提案人與連署人、議案狀態與官方關係文書 PDF/DOC 連結。資料授權：政府資料開放授權條款第 1 版。

Retrieve verifiable academic and engineering literature for a technical topic so a claim can cite a resolvable DOI instead of a vendor blog post. Queries Semantic Scholar (citation graph, abstracts, open-access PDFs) and the arXiv preprint index, merges duplicates, and ranks by citation count then recency. Returns title, authors, year, DOI / arXiv URL, citation count, and an extractive key finding taken verbatim from the abstract. Keyless; set SEMANTIC_SCHOLAR_API_KEY to escape the shared anonymous rate limit.

Estado de un pedido de nota simple registral y URL para verlo o descargar el PDF cuando esté listo. Requiere cuenta (scope `notas:read`).

Inicia el pedido de la nota simple registral de una subasta (20 €, retención: solo se cobra con PDF verificado). Requiere cuenta verificada (scope `notas:write`) y que la subasta tenga CRU/IDUFIR (`not_orderable` si no). Devuelve `pedido_id` y la `url` donde el usuario confirma el pago en el navegador (y, si el comercio para agentes está activo, `paymentLink` para pagarlo por MPP); el pago nunca se completa desde aquí. Idempotente: si ya hay un pedido vivo devuelve `pedido_existente`. Máximo 20 inmuebles al día.

Crea una sesión de checkout UCP 2026-08-25 para comprar un informe de viabilidad, una nota simple registral o una suscripción de Subastech. Productos (item.id): informe:basico:<publicId> (49 € o incluido según plan), informe:completo:<publicId> (79 € o incluido), nota-simple:<publicId> o nota-simple:cru:<14 dígitos> (20 €, solo se cobra con el PDF verificado) y plan:<starter|pro|team|enterprise>:<month|year> (la suscripción se completa en el navegador). Un producto por sesión, quantity 1. Precios con IVA. Indica checkout.buyer.email: se crea o vincula la cuenta del comprador y recibe un enlace de acceso por correo (o autentícate con un token de Subastech). Devuelve el objeto Checkout (status, line_items, totals, messages, links). Requiere meta['ucp-agent'] = { profile: 'https://<plataforma>/.well-known/ucp' } (identificación de la plataforma UCP).

Convert a PDF into structured content (tables, charts, formulas, headings, body text) using a two-stage pipeline (layout detection, then a vision-language model) rather than a single VLM call on the raw PDF -- calling a VLM on a raw PDF directly is a known-unreliable pattern for numeric tables. Measured accuracy (500-page real-world benchmark of government/corporate reports, ~51,000 table values checked): tables 95.2% digit-exact, body text 88.8%. This tool reads PDFs a VLM cannot read directly, including scanned pages and PDFs with corrupted/garbled text layers (common in older Japanese academic PDFs). For scanned Japanese documents the numbers hold up (99.4% on the same benchmark). For scanned Arabic, body text does NOT: characters are dropped mid-sentence and quantities can turn into different quantities, so body blocks from scanned Arabic are always flagged confidence:"estimated" -- tables in the same documents stayed exact in our measurement. Strong on Japanese-language documents specifically; the accuracy figures above were measured on Japanese material and are not a claim about every language. Chart values are extracted but are best-effort estimates (about 52% exact match, excluding axis tick labels) and are always flagged confidence:"estimated" in the result -- do not treat estimated chart numbers as authoritative. This is a PAID, ASYNCHRONOUS, per-page-billed operation: credits are reserved from the caller's PDFIntact balance before processing starts, and the response's _meta.credits_remaining shows the balance right after reservation. Processing takes real wall-clock time (roughly 7 seconds/page; a 500-page PDF takes about 42 minutes including a multi-minute cold start), so this tool returns a job_handle immediately without waiting -- call get_result with that job_handle to poll for completion instead of calling convert_pdf again. Always pass idempotency_key; reuse the exact same value if you retry the same request, otherwise retries can double-charge and double-process. Provide the PDF either as a public https URL (source.type="url", up to ~200MB) or inline base64 (source.type="base64", up to ~20MB) -- prefer the URL form for large files. Requires sign-in (OAuth): this session is not authenticated, so calling this tool will fail until the PDFIntact account is connected and authorized.

Fetch the status and (once finished) the structured result of a job previously created by convert_pdf. Poll this with the job_handle convert_pdf returned until _meta.state is "done" or "failed" -- do not call convert_pdf again while waiting. job_handle is scoped to the account that created it; handles belonging to a different account are rejected as not found. Requires sign-in (OAuth): this session is not authenticated, so calling this tool will fail until the PDFIntact account is connected and authorized.

Check the current PDFIntact credit balance for the authenticated account (1 page = 1 credit), plus the soonest-expiring credit lot. Useful before submitting a large PDF to convert_pdf, or after an insufficient_credits error to see how many credits are needed and get a purchase link. Requires sign-in (OAuth): this session is not authenticated, so calling this tool will fail until the PDFIntact account is connected and authorized.

Create a Gantt chart from a task list — no account or API key needed. YOU author the plan: list the tasks in execution order with realistic working-day durations and dependencies (0-based positions of earlier tasks; use { task, type, lag } for start-to-start/finish-to-finish links or lag). Milestones have duration 0. Only add a dependency where a task truly needs another one finished - independent tasks should run in PARALLEL (share a predecessor, or take no dependencies at all and start at the project start). Group tasks into top-level phases for a structured plan/WBS: the phase task gets isPhase: true, its tasks get parent = the position of the phase. LoopGantt schedules it with its critical-path engine and returns a picture of the chart, the dates, the critical path and a link where the user can view, export (PNG/PDF) and save the chart. Always show the user the link. Tasks with a due date take deadline: YYYY-MM-DD (a marker - the reply reports the fit). Use create_gantt when the user wants a chart to open, export or save; use schedule_project instead for what-if date math where nothing should be stored.

Add real Bluebeam-compatible annotation objects to a drawing PDF — counts, length/area measurements with live scales, RFI clouds, callouts — from a markups JSON you supply plus placement coordinates. Pass the PDF as an https URL or small base64; returns a marked PDF download link that expires within ~48 hours. Markups appear in Bluebeam Revu's Markups List. You decide placement; the tool guarantees the format. Nothing you submit is stored.

Generate a formal Request for Information PDF from structured fields — header, meta grid, subject, description, proposed solution, attachments, and a blank response block for the design team. You do the judgement (one issue per RFI, exact drawing references, a proposed path forward); the tool guarantees the format. Returns a download link that expires within ~48 hours. Nothing you submit is stored.

Generate a formal Nonconformance Report PDF: identification, description, the violated requirement, containment, root cause (prose or 5-Whys chain), disposition (accept-as-is/repair/rework/reject) with actions, and blank quality-review and sign-off blocks. Flags accept-as-is dispositions whose corrective action describes physical work. The disposition decision belongs to the responsible quality authority. Returns a download link that expires within ~48 hours. Nothing you submit is stored.

Stock trades disclosed by members of Congress (House and Senate Periodic Transaction Reports), by member name, ticker, transaction type or date. Returns one row per transaction with the disclosed amount range and the filing PDF.