"IRIS" matching MCP tools:

• ris_search_drafts

  ris-austria-mcp-server

  Search Austria’s federal lawmaking pipeline BEFORE promulgation — the monitoring counterpart to ris_search_gazette (what will become law). stage selects the phase: review_drafts (Begutachtungsentwürfe — draft laws a ministry has put into public review, before any government bill exists) or government_bills (Regierungsvorlagen — bills the council of ministers adopted and submitted to parliament, 2004+). Filter by query (full text), title, ministry (accepts an abbreviation like "BMF" — expanded to RIS’s exact designation; the historical name at submission time counts), in_review_on (review_drafts only — drafts whose review window covers the date; today = "what is in Begutachtung right now"), or decided_from/to (government_bills only — council adoption date). changed_since gives coarse recency. Documents are preparatory, not binding law. Ministry codes: ris_list_reference topic ministries.

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• polymarket_kalshi_spread

  Itis

  Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

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• population

  france-data-mcp

  Population d'une COMMUNE (code INSEE 5 car.), d'un DÉPARTEMENT (2-3 car.) OU d'un IRIS infracommunal (9 car.) — granularité auto-détectée par la longueur du `code`. Retourne un `LookupResult` discriminé par `found`. - IRIS (9 car., ex `751103701` = commune `75110` + IRIS `3701`) : population totale du quartier au Recensement 2022 (champ `population`, comptes bruts), + `libelle`, `code_commune`, `type_iris` (H/A/D/Z). Source : INSEE RP 2022 (table ingérée, géo 01/01/2024). Maille la plus fine (quartier) pour les villes ; en zone peu dense la commune = 1 IRIS (`type_iris` Z, code `COM+0000`). Pour le profil démographique détaillé d'un îlot ou d'un bassin (âge, CSP, familles, revenu), utiliser `profil_iris`. - Commune (5 car., ex `75056` Paris, `13055` Marseille, `2A004` Ajaccio) : PMUN/PCAP/PTOT. Source INSEE Melodi (DS_POPULATIONS_REFERENCE). PMUN = base légale DREES. Commune fusionnée → `found: false` + orientation `autocomplete_commune`. INSEE n'expose PAS les arrondissements PLM (75101-75120, 13201-13216, 69381-69389) → passer la commune-mère ou le département. - Département (2-3 car., ex `75`, `59`, `2A`, `971`) : Mayotte (`976`) ABSENTE de Melodi → `lookupNotFound`. Alias acceptés : `code_insee`/`codeInsee`/`insee`, `code_dept`/`dept`/`departement`/`code_departement`, `code_iris`/`iris` → `code`.

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• panorama_sante_territoire

  france-data-mcp

  Panorama santé d'une commune française en 1 appel (V0.9). Agrège en parallèle : population (INSEE Melodi), densités médecins + infirmiers + pharmaciens avec comparaison nationale (méthodo DREES), nombre d'établissements FINESS par famille (default ["labo","pharmacie","ehpad","mco","msp_cpts"]), et un bloc DEMANDE (V0.22.0 — profil démographique de la commune agrégé depuis ses IRIS : âge, CSP, familles, revenu pondéré, à CROISER avec l'OFFRE ci-dessus pour l'aide à l'implantation ; `demande: null` si commune hors couverture IRIS (DOM non ingéré) — pour le détail au quartier ou un bassin par rayon, utiliser `profil_iris`). Remplace 7-10 appels MCP individuels par 1 seul. Ne renvoie AUCUNE interprétation métier (pas de qualification automatique 'désert médical') — le caller LLM applique sa grille. V0.19.0 : accepte `nom_commune` (string) comme alternative à `code_insee`. `departement` (V0.19) = hint resolver UNIQUEMENT (panorama ne calcule pas par dept ; un `departement` seul lève une erreur explicite). **Granularité mixte** : les densités professionnels et la population sont calculées au niveau **commune** ; le décompte FINESS est agrégé au niveau **département** dérivé du code INSEE (limitation V0.9 — pas de RPC count_finess_by_commune encore). Le champ `niveauEtablissements` du résultat indique `"departement"` (succès), `"indisponible"` (dept indérivable, ex code DOM tronqué) — utiliser cette information pour ne pas confondre ratios commune et dept. Paris/Marseille/Lyon NON supporté : le panorama par commune dépend de la densité par commune, indisponible pour ces villes (INSEE n'expose la population qu'à la commune entière, les praticiens RPPS aux arrondissements). Un code PLM (commune-mère 75056 ou arrondissement) lève une RangeError. Pour ces villes, interroger les tools individuels au niveau `code_dept` (75/69/13). Alias acceptés : `codeInsee`/`insee`/`code` → `code_insee`. Sources : RPPS / Annuaire Santé ANS (mensuel), FINESS DREES (bimensuel), INSEE Melodi (PMUN 2023).

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• formatCitation

  Scholar Sidekick

  Format scholarly identifiers into a finished citation in a specific style. Use when the user wants a paste-ready citation string for a manuscript, slide, message, footnote, or in-line reference. Style defaults to vancouver if unspecified; ask the user before defaulting if any ambiguity exists (e.g. 'Harvard' and 'Chicago' have multiple variants — confirm which one). Supports five hand-tuned builtins (vancouver, ama, apa, ieee, cse) plus any of 10,000+ CSL style IDs (chicago-author-date, harvard-cite-them-right, modern-language-association, nature, bmj, the-lancet, etc.). Alias and dependent-style resolution apply, so 'harvard' resolves to 'harvard-cite-them-right' and the canonical ID is reported back as styleUsed. Output defaults to text; pass output=html for marked-up HTML or output=json for structured CSL items. Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: one of { text, html, items } depending on the output parameter, followed by a metadata block ({formatter: 'builtin' | 'csl', styleUsed, requestId, warnings?}) appended as a second text content item — surface this to the user when they care about reproducibility. Use resolveIdentifier instead when the user wants raw metadata to inspect or transform; use exportCitation when they want a downloadable bibliography file. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.

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• ris_search_legislation

  ris-austria-mcp-server

  Search Austrian consolidated law and English translations: federal law (scope: federal, the default), one Bundesland (scope: burgenland … wien), municipal law (municipality plus a state scope — selected norms in 6 Bundesländer), or English translations of selected federal laws (language: english, federal only, ~138 documents). One document is one § / Artikel / Anlage; fetch a whole law by filtering law_id. Searches apply the version in force today in Austria by default — set in_force_as_of for another date, include_all_versions: true for full version history, or an entered_force / left_force window for new-law and repeal tracking; the three version filters are mutually exclusive, and the applied date is echoed back in the result. query is full text (boolean UND/ODER/NICHT or AND/OR/NOT, trailing-only * wildcard); title matches title, short title, and abbreviation ("DSG"). For a specific citation like "§ 6 DSG", ris_lookup_citation resolves it deterministically instead. Consolidated text is informational, not legally binding — the authentic gazette artifact lives in ris_search_gazette.

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• ris_search_case_law

  ris-austria-mcp-server

  Search Austrian case law (Judikatur) in ONE court or tribunal per call — court is required: vfgh (Constitutional Court), vwgh (Supreme Administrative Court), justiz (ordinary courts incl. OGH, selected decisions), bvwg (federal administrative), lvwg (state administrative), dsk (data protection authority), normenliste (VwGH norm index), dok, pvak, gbk, verg, upts (party transparency), and the historical uvs, asylgh, ubas, umse, bks. Cross-court research is one call per court (calls are cheap); historical bodies are closed windows with successors — codes, windows, and Geschäftszahl examples: ris_list_reference topic courts. Filter by full-text query, cited norm ("DSG §1", "DSGVO Art32" — the highest-value filter), exact case_number (Geschäftszahl), decision date range, decision_type (headnote vs full text), decision_kind, or the court-conditional filters: issuing_body (dsk/dok/pvak/verg), court_name/legal_area/subject_area (justiz), state (lvwg/uvs), party (upts), commission/senate/discrimination_ground (gbk), subject_law (bks), collection_number (vfgh/vwgh/uvs). For a known Geschäftszahl or VfSlg/VwSlg cite, ris_lookup_citation resolves it directly.

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• ris_lookup_citation

  ris-austria-mcp-server

  Resolve a single Austrian legal citation to its canonical RIS document deterministically — no keyword search. Four routes are auto-detected from the citation shape (or forced with kind): a norm citation — section-first ("§ 6 DSG", "Art 10 B-VG"), abbreviation-first ("DSG §1", "DSGVO Art32", the shape ris_search_case_law returns in norms_cited), or a bare abbreviation like "ABGB" — resolves through consolidated federal law, or a Bundesland with a state hint, as in force today or on in_force_as_of; a gazette citation ("BGBl. I Nr. 165/1999", pre-2004 "BGBl. Nr. 194/1961", imperial "RGBl. Nr. 189/1902", or "LGBl. Nr. 61/2026" with a state hint) routes to the right federal era tier by year or to a state Landesgesetzblatt; a case number ("Ro 2026/03/0016", "G 287/2022", "14Os49/26a", "2025-0.934.677", "W256 …") is matched to its court — pass court to skip detection, and ambiguous formats probe up to two courts; a collection number ("VfSlg 19.632/2012", "VwSlg 18.000 A/2010") resolves through the VfGH/VwGH collection. Returns the single best-matching document in the same shape as the corresponding search tool, with alternatives_count when more than one matched. A citation that cannot be classified or resolved returns found: false with next-step guidance — it never throws for a miss; only an upstream RIS outage is an error. For keyword rather than citation lookup, use ris_search_legislation or ris_search_case_law.

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• ris_track_changes

  ris-austria-mcp-server

  Track every document added or changed in one RIS application within an exact date window (changed_from/changed_to), optionally including deletions (include_deleted) — the delta-sync and monitoring primitive for mirrors and watchers, and the only surface that reports removals. Unlike the search tools’ coarse, additive-only changed_since intervals, this is exact-dated and deletion-aware. application takes any RIS application code (e.g. BrKons, Dsk, BgblAuth); the four applications with a different History-feed name are mapped automatically. Each changed document comes back in a compact cross-class record — document_number (for ris_get_document), title, dates, binding_status, and rendition URLs — plus its last-changed date; removed documents come back as deleted records with a deletion timestamp. One application per call; page explicitly for large windows. Application codes and coverage: ris_list_reference topic applications.

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• bet_research

  Itis

  Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred (DFEDTARU + EFFR + CPIAUCSL) + kalshi_macro (KXFED implied probs) + recent_fed_actions (federal-register rules, last 365d); Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; hottest-year bet → climate_projection_nyc + gistemp_latest (NASA global anomaly, rank since 1880) + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires PLUS a 24h-move warning ("Market moved X.Xpp in 24h, comparable to model edge — your edge may already be priced in") when relevant; result.evidence is keyed by source. RESOLVER CONTRACT: result.market_match_confidence ∈ {high, medium, low, none}, market_match_score (0-1 token-overlap), market_match_alternatives[] (other candidate markets the resolver considered), and suggestions[] (explicit re-query hints when the match is fuzzy) — ALWAYS inspect these before trusting the analysis block, because medium/low matches can still surface other fields. PARENT_EVENT EXTRACTOR: when the bet is one leg of a partition (Yankees WS, Romania election), result.parent_event{matched_candidate, top_legs_by_price[], partition_size, placeholders_filtered} gives you the peer prices in one place — that's the headline for elections/championships. NEWS FIELDS: news entries carry _fallback_attempted / _fallback_failed_reason / retry_after_sec when GDELT 429s and GNews backfill ran or failed. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets that ARE still indexed by Polymarket (yes_price≈0, no volume, no liquidity) return status:"market_closed_or_inactive" and skip fan-out. In practice resolved markets are usually de-indexed and instead surface via the low_confidence_match path above — both routes are BLOCKING, just different mechanisms. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note. RESOLUTION-RULE RISK: market.cancellation_rule parses the void/postponement settlement out of the resolution text — refund_50_50 (shares settle flat 50¢ on void; EV-material for any entry away from 50¢, with ev_impact quantified), resolves_no_on_cancel, resolves_yes_on_cancel, carries_to_reschedule, or mentioned_unclear. null means the description never mentions cancellation. Check this before sizing sports/esports/event-occurrence bets — audited arb-bot ledgers show flat-50¢ void settlements are a recurring pure-rules loss.

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• polymarket_arbitrage

  Itis

  Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

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• suggest_questions

  Itis

  What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

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• pipeworx_feedback

  Itis

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• profil_iris

  france-data-mcp

  Profil démographique au grain QUARTIER (IRIS) — la « demande » d'un territoire (âge, CSP, familles, revenu), à croiser avec l'offre de soins pour l'aide à l'implantation. Source : INSEE RP 2022 + FILOSOFI 2021 (tables ingérées, géo 01/01/2024). Retourne un `LookupResult` discriminé par `found`. Entrée : EXACTEMENT un de `point` (`lat`+`lon`) OU `code_iris` (9 car.). `rayon_km` optionnel (0 < r ≤ 10) → DEUX modes : - SANS `rayon_km` → profil de l'ÎLOT seul (~2000 hab) sous le point / du code. `mode: "ilot"`, `revenu_median` = médiane réelle de l'îlot. - AVEC `rayon_km` → AGRÉGAT du BASSIN = îlots dont le CENTROÏDE est dans le disque (chaque îlot compté 1 fois). `mode: "bassin"`, `population_bassin`, `nb_iris_agreges`, et `revenu_median_pondere` = PROXY (moyenne pondérée population des médianes des îlots couverts — PAS une vraie médiane de bassin) + `couverture` {`revenu_pct_population`, `iris_revenu_manquants`} car FILOSOFI ne couvre que les communes ≥5000 hab. Les parts `age` (part_65_plus/75_plus) et `csp` (cadres, prof_interm, employés, ouvriers, agriculteurs, artisans_comm, retraités, autres) sont des ratios sur comptes bruts (Σ/Σ). Pour une simple population de commune/dept, utiliser `population`. `not_found` motivé si code absent ou point hors métropole / en mer.

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• exportCitation

  Scholar Sidekick

  Export scholarly identifiers to a bibliography file format ready to write to disk or paste into a reference manager. Use when the user wants a file (.bib, .ris, .nbib, .xml, .rdf, .csv) for Zotero, Mendeley, EndNote, RefWorks, BibTeX/LaTeX, Pandoc, or Excel. Format parameter is required: bib (BibTeX — LaTeX), ris (RIS — most widely supported by reference managers), csl (CSL JSON — Pandoc/Quarto), endnote-xml, endnote-refer, refworks, medline (NBIB — PubMed round-trips, clinical workflows), zotero-rdf, csv (spreadsheet-friendly), or txt (plain-text bibliography rendered with the optional style parameter — txt is the only format that uses style; the others have their own structured shape and ignore it). Accepts the same identifier formats as resolveIdentifier (DOI/PMID/PMCID/ISBN/arXiv/ISSN/ADS/WHO IRIS, prefixes tolerated), single or comma/newline-separated batch — one round trip per call. Returns: { content: string, format: string } where content is the entire bibliography in the requested format as a single string — write it to a file (.bib/.ris/.nbib/etc.) or paste it directly into the target tool. Use formatCitation instead when the user wants in-line citation text (manuscript, slide); use resolveIdentifier when they want raw structured metadata. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier.

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• resolveIdentifier

  Scholar Sidekick

  Resolve scholarly identifiers to structured CSL JSON metadata (title, authors, journal, year, identifiers). Use when the user wants raw bibliographic data to inspect, transform, or feed into another tool — not a formatted citation. Common single-shot conversions: PMID → PMCID, arXiv → DOI, ISBN → CSL JSON, WHO IRIS URL → structured metadata. Accepts DOI, PMID, PMCID, ISBN, arXiv ID, ISSN, NASA ADS bibcode, or WHO IRIS URL, with or without prefixes (PMID:, arXiv:, ISBN hyphens, https://doi.org/...). Pass a single identifier or a comma/newline-separated batch — one round trip per call. Returns: a JSON array of CSL items, each with id, type, title, author[], issued.date-parts, container-title, DOI/PMID/PMCID/ISBN/ISSN/URL when available. Use formatCitation instead when the user wants a finished citation string in a specific style; use exportCitation when they want a downloadable bibliography file. Read-only and idempotent — safe to retry. Works anonymously against the public Scholar Sidekick API (rate-limited free tier); set SCHOLAR_API_KEY (a free ssk_ key from https://scholar-sidekick.com/account) for higher limits, or RAPIDAPI_KEY for paid RapidAPI tiers. Rate limits follow your tier; the underlying REST API caches repeated identical requests and surfaces cache state in the x-scholar-cache response header.

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• ris_get_document

  ris-austria-mcp-server

  Fetch one RIS document’s full text or its rendition URLs, with explicit binding status and the amtssigniert authentic PDF surfaced wherever it exists. Address the document exactly one of two ways: document_number plus application (both copied verbatim from a ris_search_* or ris_lookup_citation result), or a document_url from a result’s content_urls. format: markdown (default — the HTML rendition converted to markdown), html (raw HTML rendition), xml (the RIS Nutzdaten XML), or urls_only (no fetch — every rendition URL, including the Authentisch PDF). Format availability varies by application and the tool degrades explicitly, never silently: consolidated law, gazettes, case law, drafts, and most sectoral collections carry full text; district and municipal promulgations and court rules (Bvb, GrA, KmGer) publish only the signed authentic PDF; party-transparency decisions and council minutes (Upts, Mrp) are PDF-only; the 1848–1940 imperial gazettes (BgblAlt) are metadata-only — for these a text-format request returns a format_unavailable notice with the usable URL, not an error. Every result carries binding_status; only authentic (amtssigniert) publications are legally binding. This tool returns content, not fresh metadata — the metadata rides the search/lookup step that produced the document number. When the markdown text overflows the byte budget the tool returns a §/Artikel/Anlage section outline (kind: outline) instead of truncating; re-call with sections:[…] naming outline entries to retrieve just those, and a name matching no section returns the outline again with a notice rather than the whole document. Markdown drops the screen-reader expansions RIS ships alongside each abbreviated citation, keeping the visible citation form; raw html/xml renditions are returned exactly as published and, carrying no markdown headings, always return in full.

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• deep_research

  Itis

  ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1391 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,305 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).

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• recent_changes

  Itis

  "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

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• polymarket_fill_risk

  Itis

  Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

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