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Use this when you need a visual capture of a web page. Renders in a real Chromium browser and returns an image. POST variant of capture_screenshot -- same params passed as JSON body instead of query string. Returns: 1. Binary image (PNG, JPEG, or WebP) 2. Custom viewport support (width/height in px) 3. Full-page scroll capture option 4. Configurable format and quality. Example output: binary image file with Content-Type image/png, typical size 200-800KB for a full page. Use this BEFORE visual QA testing, generating page thumbnails, archiving web pages, or verifying responsive design. Essential for automated screenshot pipelines and visual regression testing. Do NOT use for text extraction -- use web_scrape_to_markdown instead. Do NOT use for PDF from data -- use document_generate_pdf instead. Do NOT use for PDF from URL -- use webpage_to_pdf instead.

Use this when you need to convert a live web page to a printable PDF document. Renders in a real Chromium browser and returns binary PDF. POST variant of webpage_to_pdf -- same params passed as JSON body instead of query string. Returns: 1. Binary PDF file 2. Configurable paper format (A4, Letter, Legal, Tabloid) 3. Print-optimized layout with proper page breaks. Example output: binary PDF file with Content-Type application/pdf, properly paginated with headers/footers. Use this FOR archiving web pages as PDF, generating printable articles, saving receipts or invoices from URLs, or creating offline documentation snapshots. Do NOT use for custom documents from HTML/Markdown -- use document_generate_pdf instead. Do NOT use for screenshots -- use capture_screenshot instead. Do NOT use for web scraping text -- use web_scrape_to_markdown instead.

Search the user's connected Gmail mailboxes and return matching messages, newest first — from, to, subject, date, and a short snippet of the body. `query` uses Gmail search syntax: 'in:sent to:jane@acme.com' for messages the user sent to someone, 'from:jane@acme.com' for messages they received, plus operators like subject:, newer_than:7d, and has:attachment. So 'show me the last 5 messages I sent to jane@acme.com' is query 'in:sent to:jane@acme.com' with max_results 5. Each result carries a `starred` flag — a message the user starred matters to them, so weight it accordingly; 'is:starred' finds starred mail directly. For 'how many' questions, use total_matches_estimate in the result — it is Gmail's estimate of ALL matches, beyond the messages returned. If it reports no Gmail account connected, tell the user to connect one at /user/integrations. Rare header-only connections cannot run query search — the tool says so; answer correspondence questions from the brain for those.

List events from the user's connected Google Calendar, ordered by start time — summary, start/end, location, organizer, attendees and their RSVP status, and a meeting link when there is one. With no time range it returns upcoming events from now. `time_min` and `time_max` are RFC3339 timestamps ('2026-08-19T00:00:00Z'), so 'what's on my calendar tomorrow' is time_min/time_max spanning that day; past ranges work too. `query` free-text matches event titles, descriptions, and attendees. For 'how many meetings…' questions over long ranges (a quarter, a year), set count_only=true — it sweeps the whole range and returns the total plus a per-month breakdown instead of the events themselves, so a 12-month count is one call. By default this reads the primary calendar; to read a named calendar ('my Family calendar'), first get its id from list_google_calendars, then pass calendar_id. If the result says no Google account is connected (or the account lacks calendar access), show the user the message and link them to /user/integrations/gmail.

Set up a standing search the user wants watched — 'track LinkedIn posts that mention hubspot', 'track tweets mentioning @dharmesh', 'watch acme.com/pricing for changes'. query is what to watch for; tracker_type says where to watch (LinkedIn posts unless they ask for tweets/X or a specific page URL — a URL to watch means web_page, with the URL in url and query as a short label for it). linkedin_post and twitter_search requests become a daily cloud agent that emails a digest of new posts; web_page creates a tracker in their brain that runs daily and emails changes, filtered by the prompt. Always give the user the returned page_url as a link — that page is where they review and manage it.

Set a dated follow-up about an object in the user's graph — 'follow up with Jane in March'. Creates a follow-up fact carrying follow_up_at (ISO 8601, usually in the future) and an optional note, connected to the object it's about. Interim shape: there is no dated query tool yet, so to read follow-ups back ('what's due this week?'), list the user's fact objects and filter on json_data.follow_up_at yourself.

Read back objects a skill wrote earlier, filtered precisely. Use this when you need to know whether something is already recorded rather than to find something by name: has this engagement already been flagged, was this client surfaced today, is there a plan for this week. Filters on type, on the source that wrote the row, on text within the name or description, and on a created-at window in days. Sorts newest, oldest or by name, and pages with offset. For a keyword or semantic hunt across the graph use search_graph_objects; for browsing a whole type use list_graph_objects.

Query the user's HubSpot contacts — the people synced from the HubSpot portals they've connected. Use this for any question about their CRM contacts: engagement filters ('show me people with more than 10 page views'), lifecycle and pipeline ('how many customers do I have?', 'leads with an open deal'), firmographics ('contacts at Google', 'people in Boston'), attribution ('which source brought the most contacts?'), email activity, deal amounts, lead scores, or form conversions. Answered by generating a read-only SQL query over the synced contact table, so it returns columns and rows rather than prose — summarize the rows for the user, and say how many there were. If it reports no contacts synced, tell them to import at /hubspot/import. Keep the question under 500 characters.

Return origin, host, and path for a URL. Query and fragment are dropped.

Count characters in a search query. Query discarded.

Read a public article or YouTube URL and return only the passages relevant to your query, each anchored to its paragraph and labelled with the section it sits under. Use this instead of get_article whenever you have a specific question about a link — it answers in a fraction of the tokens and the anchors stay citable.

Use the same discovery catalog and ranking as smry's Discover feeds page. Browse suggested sources with no query; search websites, RSS, Atom, podcasts, Reddit, and YouTube by topic; create a focused Google News source; or discover every feed published by a site URL. Use sort=popular for popularity ordering. This only discovers sources; use follow_feeds to follow results in an existing or new collection.

Search this account's articles, websites, books, emails, PDFs, social posts, videos, podcast episodes, and documents. For a normal text search, pass only query and limit. "Triage my inbox" is {"status":"inbox","limit":10}; "saved this week" is {"saved_after":"7d"}. Matching is shared with app search and REST, including spelling recovery (approximate=true). Optional filters are combined with AND: omit every filter the user did not explicitly request. Filter by exact tag, kind, capture method, format, or lifecycle; set view=history for recently read items. Items are ordered by most recent status change first (history view: last read first); continue with nextCursor. Item IDs select later tools and are not smry.ai routes; cite only each exact returned source URL.

Read followed feeds. "What's new?" is {"since":"1d"}: newest published first, one line per entry with format:"compact". Other arguments are optional; add where.collection, where.source.include/exclude, where.unread, or where.match when requested. per_source_limit produces a bounded fair sample across pages; omit it to retrieve every matching article. select:"sources" returns fetch_status and last_fetched_at separately from publisher activity (health, silent_days, entries_7d/28d). Quiet publishers can have working feeds. select:"aggregate" returns grouped counts with optional trends. Classification-filtered queries report classification_coverage: pending articles have not been assessed, not rejected. Times accept "7d"/"36h"/"now" or ISO dates. Example: {"since":"1d","per_source_limit":3,"limit":40,"format":"compact"} Example: {"select":"entries","where":{"unread":true,"collection":["Research"]},"limit":10} Example: {"select":"sources","having":{"silent_days":{"gte":30}},"limit":10} Example: {"select":"aggregate","group_by":"collection","where":{"discovered_after":"7d"}}

Find public feeds by topic or find a site's published feeds. This is the compact Developer API discovery adapter; use search_feeds for language, ranking, and source-type controls. Discovery does not subscribe; pass result feedUrl values to follow_feeds. Example: {"query":"https://www.nasa.gov","mode":"site"}

Creates a Collection-compatible news query. Google News RSS is the current adapter and is intentionally hidden behind this durable product type. Example: {"query":"open source databases","collection":"Research"}

107 questions this archive can answer, each with the SQL that answers it. Every one is executed against the database on every build, so none of them is a claim. Start from the nearest one and edit it rather than writing a query from scratch.

Any question the other tools do not cover, as one read-only SQL statement over the archive database. SELECT or WITH only; a LIMIT is imposed if you omit one. Call `read_first` before computing anything and `list_datasets` to find table names. A query estimated to read more than 250,000 rows is refused — narrow it with a WHERE, or ask for one table at a time.

Return origin, host, and path for a URL. Query and fragment are dropped.

Count characters in a search query. Query discarded.

Check the progress/status of a Patient's document query (download + FHIR conversion counts). Medical API: POST /medical/v1/document/query with only patientId (no facilityId) returns current status without starting a new query.

Get the status of the Patient's consolidated-data (FHIR) queries. Medical API: GET /medical/v1/patient/{id}/consolidated/query.

Creates a Patient in Metriport (writes PHI and initiates health-information-exchange queries). Medical API: POST /medical/v1/patient (facilityId is a required query param).

Starts a document query — retrieves the patient's medical documents from connected HIE networks. Returns a requestId; results arrive asynchronously. Medical API: POST /medical/v1/document/query (patientId and facilityId are required query params).

Starts a consolidated-data (FHIR) query for the patient. Returns a requestId; the bundle is delivered asynchronously (webhook). Medical API: POST /medical/v1/patient/{id}/consolidated/query.

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).

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.

Query this account's Kamy Trace records, newest first, filtered by feature, status, provider, tag, or time window. Returns record metadata — model, tokens, latency, status, content hash, recorded_at — plus next_cursor for paging; it does not return the stored prompt and output bodies. Use it to answer questions like 'how many flagged calls last week?' or to locate a specific record's id before opening it in the dashboard. Read-only. Requires a Kamy API key with the trace:read scope.

Search Postapp's library of instantly published single-file web apps. Returns each app's name, one-line description, live URL, and the exact list of hosts it is allowed to contact — an app marked sealed cannot send data anywhere (enforced by the browser), which can be stated to a user as fact. Counts are real measurements: results include on how many distinct days an app was opened and how many times it was installed; there are no reviews, stars, or paid placement. An empty query lists the whole shelf. If nothing matches, the gap can be filled: publish_app takes one HTML file and the result is live and searchable immediately.

Run a database query on one of your servers — passwordless. It executes the engine's own client on the host over Termalin's keyless tunnel, using the database's local trust (Postgres peer auth via `sudo -u postgres`, MySQL/MariaDB unix-socket via `sudo mysql`, redis-cli, mongosh, sqlite3) — so no database password is needed or stored anywhere. Read-only by default: only SELECT/SHOW-style statements run unless allowWrites is set (full-access keys only). SQL engines return CSV/TSV with a header. For MongoDB pass a shell expression, e.g. db.products.find({}).limit(20).toArray().

List the tables / collections / keys of a database on one of your servers — passwordless, over the same local-client path as data_query.

Full-text search the ACC Docs repository of a project for drawings, specs, submittals, and other files via the APS Data Management search endpoint. When to use: The user wants to find a document by keyword (filename, sheet number, or metadata match). E.g. 'find the latest A-201 sheet' or 'search for mechanical specs on Tower project'. When NOT to use: Do not use to upload a file (use acc_upload_file); do not use to fetch issues/RFIs. If you already have a document URN, fetch it directly with an agent that has Data Management folder/item access. APS scopes: data:read account:read. No write scope required. Rate limits: APS Data Management ~50 req/min per app per endpoint; pageable (limit 200 upstream). Avoid tight query loops. Errors: 401 (APS token expired — refresh); 403 (user lacks Docs view permission on the project); 404 (project_id not found — verify 'b.' prefix and hub membership); 422 (invalid filter syntax — simplify query text); 429 (rate limit — back off 60s); 5xx (ACC upstream — retry with jitter). Side effects: None. Read-only and idempotent.