Esef Filings

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 2026-10-19 · checked 2026-10-19 10:52 UTC

Tool changes

• 2026-10-19pipeworx_feedbackremoved

  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). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. 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.

• 2026-10-19recent_changesremoved

  "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.

• 2026-10-19ask_pipeworx_groundedremoved

  Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 6,984 across 1834 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

• 2026-10-19esef_entity_filingsremoved

  List every annual report one company has published to the XBRL International filings index, resolving a company name, LEI, or national registration number to the filer. Answers "what years has Citycon filed?" or "give me Nokia's latest annual report". Returns the resolved company (name, identifier, and how the match was made) plus each filing with period end, country, regime, validation error/warning counts and links to the xBRL-JSON, HTML report and viewer. Covers 25,640 filings in two regimes: ESEF (~16,000 annual financial reports from 19 European countries — AT BE CY CZ DK ES FI FR GB GR IS IT LT NL NO PL PT RO SE) and UAIFRS (~9,600 Ukrainian IFRS filings, country UA). Pass `country` or `regime` to pin the scope you mean. Portuguese (PT), Spanish (ES) and Norwegian (NO) ESEF reports are also read directly from where each country publishes them — CMVM for Portugal, CNMV for Spain, Oslo Børs NewsWeb for Norway — so PT, ES and NO coverage follows official publication (typically within a day) rather than the index's months-long lag; each row names its `source` and those rows carry the official `published_at`. Swedish (SE) reports are likewise read from Finansinspektionen (FI), the Swedish OAM, which is the only source for Swedish FY2025 reports, Belgian (BE) reports from the FSMA's STORI database, the Belgian OAM, Maltese (MT) reports from the Malta Stock Exchange OAM, the only source for Maltese FY2025 reports, Croatian (HR) reports from HANFA's SRPI, the Croatian OAM and the only source for Croatian FY2025 reports, Hungarian (HU) reports from the MNB's Közzétételek site, the Hungarian OAM and the only source for Hungarian FY2025 reports, Lithuanian (LT) reports from oam.lt, the Lithuanian OAM run by Nasdaq Vilnius, as well as the index, Romanian (RO) reports from the ASF OAM, the only source for Romanian FY2025 reports, Cypriot (CY) reports from the Cyprus Stock Exchange public OAM, the only source for Cypriot FY2025 reports, and Latvian (LV) reports from CSRI, the Latvian OAM, the only source for Latvian FY2024 and FY2025 reports. Luxembourgish (LU), Slovenian (SI) and Estonian (EE) reports are also answered directly from the LuxSE OAM, SEOnet or the Estonian FSA's OAM for each request, because these three OAMs' terms require the operator's consent for commercial reuse of their documents beyond ordinary access; a lookup made once on a caller's behalf is not that. Greek (GR) and Irish (IE) reports are likewise answered directly from Euronext Athens and the Euronext Dublin OAM for each request — these two sites' terms forbid bots and automated access outright rather than just reuse, so these are Bruce-authorized live lookups rather than a re-derivation of the usual reasoning, kept live and never mirrored for the same reason. Bulgarian (BG) reports are answered directly from BEIS, a Bulgarian disclosure agent whose terms ask only for attribution (unlike Bulgaria's other disclosure agents, which this pack does not call) and covers only the roughly three issuers that use it. None of GR/IE/BG carry machine-readable facts (esef_filing_facts declines a live-lookup id and points at its `package_url`/`source_url`); SI is limited to the ~20 most recent Slovenian annual-report announcements; IE rows carry no `period_end` (Irish fiscal year ends vary by issuer); GR's `period_end` is inferred from the filing's reporting year, not stated exactly, and flagged `period_end_inferred`. All six (LU, SI, EE, GR, IE, BG) are pinned-country lookups only — pass `country` explicitly. The same annual report is frequently indexed once per language edition (a Finnish and an English row for one financial year), so results are also grouped into distinct reports with the English edition preferred, and both a filing count and a distinct-report count are returned.

• 2026-10-19forgetremoved

  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.

• 2026-10-19recallremoved

  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.

• 2026-10-19ai_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.

• 2026-10-19generate_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.

• 2026-10-19pipeworx_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.

• 2026-10-19research_rowremoved

  Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).

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.