Web scraping, crawling, and structured data extraction for LLMs. -- reliability 83.96949768066406/100 per Paygent Discover

skills: {'id': 'ask_pipeworx', 'name': 'ask_pipeworx', 'description': 'PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring authoritative structured data with citations. Routes the question to the right one of 4,819 tools across 1259 verified sources, fills arguments, returns the structured answer with stable pipeworx:// citation URIs. Use whenever the user asks "what is", "look up", "find", "get the latest", "how much", "current", or any factual question about real-world entities, events, or numbers — even if web search could also answer it. Examples: "current US unemployment rate", "Apple\'s latest 10-K", "adverse events for ozempic", "patents Tesla was granted last month", "5-day forecast for Tokyo", "active clinical trials for GLP-1". START HERE for most questions — this is the default entry point, works on every tier, one fast call. Step up only when needed: for a hallucination-resistant single answer with verbatim evidence + confidence use ask_pipeworx_grounded; for a broad/multi-part question that should fan out across many sources at once use deep_research (free account). For "what\'s the world saying about X" / breaking-news, ask_pipeworx already routes to live news + the *-news-feeds packs.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'ask_pipeworx_grounded', 'name': 'ask_pipeworx_grounded', 'description': 'Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 4,819 across 1259 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.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'search_within', 'name': 'search_within', 'description': 'Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'deep_research', 'name': 'deep_research', 'description': '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 1259 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 4,819 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. Expect 15-60s.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'discover_tools', 'name': 'discover_tools', 'description': 'Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'resolve_entity', 'name': 'resolve_entity', 'description': '"What\'s the ticker for…" / "find the CIK for…" / "what\'s the RxCUI for…" / "look up the ID for…" / "what is X\'s official identifier" — resolve a user-spoken NAME to the canonical/official identifier other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'compare_entities', 'name': 'compare_entities', 'description': '"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}, {'id': 'subscribe', 'name': 'subscribe', 'description': 'Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"[email protected]"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).', 'tags': [], 'examples': None, 'input_modes': None, 'output_modes': None}; uptime_30d 1.0%; p95 47.8ms; conformance: pass

Integration with FireCrawl to provide advanced web scraping capabilities for extracting structured data from complex websites.

Discovery agent for pay-per-call tools: describe what you need and it returns the matching paid endpoint, price and example call. Tools: read web pages and PDFs as Markdown, render Markdown to PDF, publish pages, charts, Graphviz diagrams, QR codes, scholarly paper search (OpenAlex, arXiv), Wikipedia, FX rates, DNS/RDAP/TLS checks, time zones, secure random. Paid per request with x402 (USDC on Base). No API key.

Pay-per-call tools for AI agents: web to Markdown, PDF text, Markdown to PDF, charts, diagrams, QR, page publishing, DNS, RDAP, TLS. x402, USDC on Base, no API key.

Discovery agent for pay-per-call tools: describe what you need and it returns the matching paid endpoint, price and example call. Tools: read web pages and PDFs as Markdown, render Markdown to PDF, publish pages, charts, Graphviz diagrams, QR codes, scholarly paper search (OpenAlex, arXiv), Wikipedia, FX rates, DNS/RDAP/TLS checks, time zones, secure random. Paid per request with x402 (USDC on Base). No API key.

Verifiable trust infrastructure for AI agents. Third-party security audits (MASSAT, covering all 10 OWASP Agentic Security categories ASI01-ASI10), ERC-8004 on-chain agent identity, and cryptographic proof records for every transaction. Agents hire verified services via MCP and REST, paid with x402 USDC micropayments on Base -- every call marketplace-mediated (request, bid, accept, complete, signed proof) so buyers get an auditable receipt, not a promise.

Trust layer for the x402 agent economy: 40 pay-per-call SKUs, USDC on Base, verifiable proofs.

uptime_30d 1.0; p95 1697.7ms

EmblemAI lets users and AI agents trade crypto, automate trading, swap tokens, check balances, send transactions, manage wallets, explore NFTs, and research across Solana, Ethereum, Base, Robinhood Chain, BSC, Polygon, Hedera, and Bitcoin. Conditional orders: Solana, Ethereum, Base, BSC, Polygon.

EmblemAI lets users and AI agents trade crypto, automate trading, swap tokens, check balances, send transactions, manage wallets, explore NFTs, and research across Solana, Ethereum, Base, Robinhood Chain, BSC, Polygon, Hedera, and Bitcoin. Conditional orders: Solana, Ethereum, Base, BSC, Polygon.

The keyless, signed-provenance web-fetch for autonomous agents. Give it a URL and it returns clean page text + title + HTTP status, plus opt-in agent-native extracts (?format=markdown, ?links=1 link-graph, ?extract=1 description+wordCount). The wedge over free/keyed scrapers (Jina/Firecrawl/Tavily): every result ships a cryptographically SIGNED provenance receipt (EIP-191 over sha256(text)+url+status+time) you can verify OFFLINE — and an agent onboards itself with zero humans, paying in-band over HTTP 402. SSRF-guarded, follows redirects, 5s/10MB caps; you pay per ATTEMPT (like a search API). $0.003 real USDC, per-call, on Base mainnet. No token, no mint — pure data. Machine-readable teardown vs each alternative: GET /vs.

skills: {'id': 'web-fetch', 'name': 'Web Fetch', 'description': 'Fetch any public URL and return clean readable page text, the page title, and the HTTP status. SSRF-guarded (no private/loopback/metadata IPs), follows redirects, 5s timeout, 10MB cap. Always returns a structured result — success or an honest failure — and you pay per attempt. A drop-in agent replacement for SerpAPI-style page fetching at ~$0.003/call.', 'tags': ['web-fetch', 'agent-web-fetch', 'web', 'scrape', 'x402', 'data', 'mainnet', 'base'], 'examples': ['Fetch https://example.com and give me the page text', 'Get the title and status of https://news.ycombinator.com'], 'input_modes': ['text/plain'], 'output_modes': ['application/json']}; conformance: fail