Oneinfo Storage

Quality – / 100not scored

Not scored: fewer than three checks apply, usually because no remote answered a credential-free probe or the server is a local package.

Tool list unknown · tools last changed 2026-10-18 · checked 2026-10-20 15:57 UTC

Tool changes

• 2026-10-18oneinfo_get_disclosureremoved

  Fetch a single 1INFO disclosure by its protocolCode id and publication date, as returned by oneinfo_search_disclosures. This source has no by-id-only lookup endpoint, only by-day listings, so both id and date are required. Returns the shaped record — company, title, category, timestamp, and the document URL (with the .pdf-suffix / fiscal-year gotchas already handled).

• 2026-10-18oneinfo_search_disclosuresremoved

  Search Italian regulated company disclosures from 1INFO, one of Italy's two EU Transparency Directive Officially Appointed Mechanisms (the other is eMarket Storage — use emarket-storage's emarket_search_disclosures for issuers covered there instead, e.g. WEBUILD/SAIPEM). Identify the issuer with company (free-text name, resolved against 1INFO's own 314-issuer list) or ndg (1INFO's internal numeric issuer id, from a prior result) — there is no ISIN field on this source, and LEI only appears embedded in the filename of XBRL-tagged annual-report ZIPs (see the returned document_url for those). date_to IS INCLUSIVE (the last local-calendar day you want, Europe/Rome). COVERAGE: 1INFO issuers only — a second Italian mechanism, eMarket Storage, covers a separate set (e.g. WEBUILD) and is not included; an unmatched company name is reported as "not a 1INFO issuer", not as an error. NO SERVER-SIDE ISSUER FILTER exists on this source, so a company/ndg search scans recent storage-date-ordered pages client-side up to a bounded depth — the response's scanned.oldest_date_local says honestly how far back it looked; a rarely-filing issuer may need a narrower/older date_from to surface. Category codes: 1.1=1.1 Relazione finanziaria annuale e relazione di revisione annuale; 1.2=1.2 Relazioni finanziarie semestrali e relazioni di revisione semestrali/revisioni limitate; 1.3=1.3 Pagamento ai governi; 2.1=2.1 Stato membro d'origine; 2.2=2.2 Informazioni privilegiate; 2.3=2.3 Notifiche di partecipazioni rilevanti; 2.4=2.4 Acquisizione o cessione di azioni proprie dell'emittente; 2.5=2.5 Totale dei diritti di voto e del capitale; 2.6=2.6 Modifiche dei diritti inerenti alle categorie di azioni o di valori mobiliari; 3.1=3.1 Ulteriori informazioni previste dalla regolamentazione nazionale; MANTRA=MANTRA — Internal Dealing (operazioni di persone rilevanti e strettamente associate); MANRSS=MANRSS — Relazione sulla gestione, inclusa la dichiarazione di sostenibilità; REGEM=REGEM — Altre informazioni regolamentate (art. 82-ter Regolamento Consob 11971/1999); DOAG=DOAG — Relazione finanziaria; DOOS=DOOS — Documenti operazioni straordinarie; DOAL=DOAL — Documenti diversi. Returns disclosure EVENTS (title, company, category, timestamp, document link) — NOT extracted XBRL facts; for annual-report XBRL facts use esef-filings (Italy: ~6 days behind 1INFO). Half-year reports have NO XBRL-facts source anywhere else, since ESEF is annual-only.

• 2026-10-18forgetremoved

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

• 2026-10-18recallremoved

  Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

• 2026-10-18rememberremoved

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

• 2026-10-18scan_competitor_ai_presenceremoved

  Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

• 2026-10-18ai_visibility_checkremoved

  Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.

• 2026-10-18generate_llms_txtremoved

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

• 2026-10-18pipeworx_trendingremoved

  What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

• 2026-10-18classify_rowremoved

  Cheap categorization: given a company and a list of candidate labels, decide which labels apply — the most common GTM/AI usage shape (tagging a list by industry, ICP fit, etc.), one small model call. Same evidence contract as research_row: each label comes back {label, applies, evidence_url, quote, status: found|inferred|not_established} — "found" only when the model's quote is independently verified as a verbatim substring of the text used. Pass text directly (cheapest — no fetch) or entity.domain to fetch the homepage once as a fallback. No text and no domain means every label is not_established with no model call made.

Showing the latest 10. Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.