Sec Beneficial Ownership

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 2026-10-16 · checked 2026-10-21 00:32 UTC

Tool changes

• 2026-10-16sec_13d_amendment_diffremoved

  Given one 13D/A or 13G/A amendment (issuer + accession_number), find the SAME reporting group's prior filing in the chain and diff what changed: percent of class, aggregate shares owned, sole/shared voting & dispositive power (per reporting owner, matched by CIK or name), and — for 13D — whether the Item 4 purpose text changed. Walks back through the issuer's filing history (bounded, never a bulk crawl) matching on reporting-owner identity, since EDGAR does not carry an explicit "previous accession" link for this form family. Reports `prior_filing_found: false` honestly if no matching prior filing turns up within the scan bound, or if the chain predates the structured-XML rule (diffing free text is not meaningful).

• 2026-10-16sec_13d_filingremoved

  Parse ONE Schedule 13D or 13G filing by issuer + accession_number (get the accession_number from sec_13d_filings). Returns every reporting owner (the "group members") with percent of class, sole/shared voting power, sole/shared dispositive power, and aggregate shares owned; for Schedule 13D, also Item 4 — the free-text "Purpose of Transaction", which is where an activist states its intent (board seats, a merger, liquidation, or "no plans"). Filings from before SEC's 2024 structured-XML rule have no machine-readable fields — this returns `structured: false` plus the bounded plain text of the filing instead of silently returning empty data.

• 2026-10-16sec_13d_filingsremoved

  List Schedule 13D / 13G beneficial-ownership filings (and their amendments, 13D/A and 13G/A) for one issuer — AUTHORITATIVE source for "who owns 5%+ of $TICKER" and "has an activist filed a 13D on this company". Takes a ticker or company name (auto-resolved to CIK) or a CIK directly. Each row flags `structured: true/false` — filings from SEC's 2024 XML rule onward are structured and feed straight into sec_13d_filing; older ones are plain text/HTML only. Use sec_13d_filing on any accession_number returned here to get the actual reporting-owner data (percent of class, voting power, purpose).

• 2026-10-16forgetremoved

  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.

• 2026-10-16recallremoved

  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.

• 2026-10-16rememberremoved

  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.

• 2026-10-16scan_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.

• 2026-10-16ai_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.

• 2026-10-16generate_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.

• 2026-10-16pipeworx_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.

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.