Skip to main content
Glama
307,365 tools. Last updated 2026-07-18 23:18

"author:haju-xp" matching MCP tools:

  • Returns full loan contract detail by id (GET /loans/:loanId): interestRates[] (taxType, ratePercentage, indexer), contractedFinanceCharges[], balloonPayments[], warranties[], installments schedule (installmentsCount, paidInstallments, numberOfInstallmentsRemaining, installmentFrequency), amortizationScheduled, CET, ipocCode and dates. Use after openfinance_list_loans to deep-dive on a specific contract. Pass `loan_ids` as an array (1-50). `{ results, errors }` batch shape.
    Connector
  • Search X by keywords. type picks the mode: recent (default) is the deep chronological sweep and keeps paginating as far as you follow the cursor; popular returns the highest-engagement tweets for the query; people finds accounts and returns a single page (no cursor). Advanced query operators pass through verbatim, e.g. "from:nasa", "min_faves:100", exact phrases in quotes -- there is no separate date parameter, so use since:/until: operators for time windows. Costs 6 credits per page; a cursor page is a NEW call priced the same way, so a deep sweep costs linearly in pages. Returns tweet summaries (text, author with follower count, views, likes, retweets, replies, created_at, url, id) with a cursor. Fetch one tweet's full detail with x_get_tweet and an account's timeline with x_get_tweets. For comment-level sentiment inside topic communities, reddit_search type=comments is usually the sharper instrument.
    Connector
  • Fetch one tweet by id with full engagement metrics: views, likes, retweets, quotes, replies, bookmarks, language, and the quoted tweet inline when there is one. tweet_id is the numeric id from a tweet URL (the digits after /status/) or from any other X tool's results; full tweet URLs are accepted too. Costs 4 credits. Use this to verify engagement before citing a tweet or to read a quoted thread hop by hop. It returns a single tweet, not the conversation around it: for the author's other tweets use x_get_tweets, and to find tweets by topic use x_search.
    Connector
  • Identify what an X (formerly Twitter) URL points at before fetching it. Give any x.com or twitter.com URL (mobile links, query params, /i/web/status forms are fine); get back {type: profile|tweet, id, handle, canonical_url}. Tweet URLs yield the numeric id for x_get_tweet; profile URLs yield the handle for x_get_profile or x_get_tweets. Costs 2 credits and parses offline without fetching the page. t.co short links cannot be expanded offline and return INVALID_INPUT telling you so; expand them in your own browser step first. Skip this tool when you already have a handle or tweet id: the other X tools accept those directly.
    Connector
  • Use this when the signed-in user asks about their own streak, XP, words mastered, recent activity, or 'how am I doing'. Auth-only personal dashboard. Renders the interactive Vocab Voyage progress widget on supporting hosts; falls back to markdown elsewhere. Anonymous callers receive a sign-in prompt. Do not use for global stats or other users' progress.
    Connector
  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
    Connector

Matching MCP Connectors

  • Connect your XP account to AI via Brazil's Open Finance: balances, statements, cards, investments. R

  • Code::Stats public coding-XP profiles (codestats.net)

  • 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).
    Connector
  • 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 1321 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 5,018 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. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • 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 1321 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 5,018 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. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).
    Connector
  • Publish a post to a connected X account via the official X API (POST /2/tweets). Call x-twitter.connected_accounts first. If accounts is empty, the user must connect an X account at https://vee3.io/dashboard/connections before posting. Agents cannot complete OAuth; ask the user to connect, then call x-twitter.connected_accounts again. Pass user_id or user_name to target a specific account, not both. Omit both to use the default connected account. At least one of text, poll, media, or card_uri is required. Supports text, polls, media attachments, reply settings, paid partnership disclosure, AI-generated labels, super-follower exclusivity, nullcast posts, cards, communities, and direct-message deep links. To attach media, upload files with meta-tools.upload_file and the @vee3/upload CLI, then pass file_name values returned by meta-tools.list_uploaded_files in the media array (up to 4 files). Only files listed by list_uploaded_files can be attached. poll, media, and card_uri are mutually exclusive in the X API. Token pricing: 60 tokens base for text posts. Posts whose text includes a URL are billed 1000 tokens base instead. Attaching only media (an image or video) without a URL in the text does not trigger the URL rate. Each attached image adds 50 tokens. Each attached video adds 150 tokens plus 50 tokens per 5 MB of video size. X rate limit: 100 POST /2/tweets requests per connected user per 15 minutes. Wait and retry if posting is temporarily blocked. If X authorization fails, reconnect the account in the Vee3 dashboard. Read the error message when X rejects a post and adjust the request.
    Connector
  • List X (Twitter) accounts connected to the authenticated Vee3 account for write capabilities. Returns user_id, user_name, display name, avatar URL, and whether each account is the default. Use user_id or user_name on future write calls, or omit both to use the default account. If accounts is empty, the user must connect an X account at https://vee3.io/dashboard/connections before write capabilities work. Agents cannot complete OAuth; ask the user to connect, then call this tool again. Cost = 0 tokens.
    Connector
  • Returns accounts for a bank connection: BANK (checking/savings) and CREDIT (credit card) with balance, number, type, subtype, bankData, and creditData. Also returns `bank` (the brand/connector name like 'Nubank Empresas' — same shown in the dashboard UI) and `connector_id`. Note: each account's `name` is the legal entity that issues the account (e.g. 'Nu Pagamentos S.A. - Instituição de Pagamento'), which is not the same as the brand — when referring to the bank in user-facing text, use `bank`. OMIT `item` to list accounts across ALL linked banks at once — the response aggregates every connection's accounts into `results`, each row tagged with its own `bank`/`connector_id`/`item_id` (use this when the user asks for 'my accounts/cards' without naming a bank). Pass `item` to target a single bank (response carries `bank`/`connector_id`/`item_id` at the root). CREDIT (credit card) `balance`: its meaning is CONNECTOR-DEPENDENT — some banks report the current open-bill partial, others the full revolving/installment debt — so do NOT treat `balance` as 'this month's bill'. The open billing cycle is defined by `creditData.balanceCloseDate` (when it closes) / `balanceDueDate` (when it's due). For a standardized open-bill amount and total debt that mean the same across connectors, use openfinance_list_credit_card_bills (`open_bill` + `total_pending_debt`, derived from PENDING transactions); closed bills come from that same tool's `results`. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a bank in this response: balances and credit limits may be unreliable (incomplete or wrong, e.g. a credit limit near 1,00) even with the connection UPDATED, until the provider recovers. Do not present those values as real.
    Connector
  • Returns transactions for a bank account (BANK or CREDIT type). For CREDIT (credit card) accounts, this is the ONLY way to get itemized transactions (purchases, subscriptions, etc.). Each credit card transaction MAY carry `creditCardMetadata.billId` pointing at a bill from openfinance_list_credit_card_bills, but this is a per-connector HINT, not authoritative: some connectors (e.g. Nubank) populate it sparsely (many transactions and installments arrive with no billId) or inconsistently (the same payment tagged to more than one bill). Do NOT reconstruct a bill's total by summing transactions by billId — the bill's own `totalAmount` from openfinance_list_credit_card_bills is the source of truth. CREDIT PENDING vs POSTED varies by connector: where the bank exposes future-dated `status:'PENDING'` installments, those represent the OPEN bill plus future bills (future months); where it does NOT, only the last closed bill's POSTED items appear until ~closing. Same query, different coverage per bank (upstream). To get a standardized open-bill total / total debt regardless, use openfinance_list_credit_card_bills (`open_bill` / `total_pending_debt`). Supports from/to date filters (ISO YYYY-MM-DD) and an optional keyword filter via `search_queries` (case- and accent-insensitive substring match against description and merchant name, OR semantics across multiple terms). When `search_queries` is set the tool aggregates up to 5000 transactions within from/to before filtering — narrow from/to if `truncated:true` is returned. PAGINATION: OMIT `page` (the default) to get ALL transactions in the from/to range in one call — the tool auto-paginates the upstream and returns them under a single logical page (`page:1`, `totalPages:1`), up to a 5000 ceiling (`truncated:true` + warning if exceeded, then narrow from/to). Pass an explicit `page` (with `page_size`, max 500) only if you want to walk pages manually instead. On upstream errors, returns { total:0, results:[], warning, error } instead of throwing. `detail` controls how much per-row data you get (default `'compact'` = slim, cheap). Use `detail:'rich'` to enrich each row (when the bank connector provides it) with `merchantInfo` (estabelecimento: businessName/razão social, cnpj, cnae, category — useful for auto-classifying spending) and extra `creditCardMetadata` fields: `billId` (a per-connector HINT toward the transaction's bill — sparse/inconsistent on some connectors like Nubank, so do NOT sum by it to get a bill total; use the bill's `totalAmount` instead), `purchaseDate`, `payeeMCC`, `feeType`/`feeTypeAdditionalInfo`, `otherCreditsType`/`otherCreditsAdditionalInfo`. Use `detail:'raw'` to get the FULL untouched Pluggy transaction object (everything Pluggy returns, un-normalized — heaviest, for when you need a field we don't project). 'rich'/'raw' add tokens per row and coverage varies by bank/Open Finance, so keep the default for normal listings. For the card's statement closing/due dates use openfinance_list_accounts (`creditData.balanceCloseDate` / `balanceDueDate`). The response opens with an `account` echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH account/bank these transactions belong to. When more than one bank is connected, ALWAYS cross-check the echo against the account you intended to query and name the bank when presenting results — never attribute one bank's transactions to another. If total is 0 for a CREDIT account, check the connection health via openfinance_get_item_status — `statusDetail.creditCards.isUpdated: false` means the credit card sync failed and a force sync (openfinance_force_sync) or reconnection may be needed. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a connected bank: transactions may come back incomplete or wrong until the provider recovers, and reconnecting does not fix it. Bulk support: accepts account_ids for batched execution.
    Connector
  • Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call. Resolves the connection's accounts internally and fans out their transactions, so you do NOT need to call openfinance_list_accounts first nor carry account_id uuids between calls. Pass `item` (connector_id, connector_name or item_id) to target one bank, or OMIT it to analyze ALL linked banks at once. `from`/`to` are ISO dates (YYYY-MM-DD). Default `granularity:'monthly'` returns a COMPACT summary (no raw rows): total entradas, saídas, saldo_liquido, monthly evolution (`por_mes`), and `top_despesas`/`top_recebimentos` (largest N each), plus a per-account breakdown (`by_account`). Use this for 'análise anual/mensal', 'fluxo de caixa', 'entradas e saídas', 'maiores gastos/recebimentos'. Set `granularity:'raw'` to ALSO get every consolidated transaction (heavier — only when itemized rows are needed); combine with `detail:'rich'` to enrich those rows with merchantInfo (cnpj/cnae/businessName/category) + extra creditCardMetadata (billId, purchaseDate, fees), or `detail:'raw'` for the full untouched Pluggy object per row, when the connector provides them. `type` filters BANK or CREDIT accounts. On a connection with many transactions the scan caps at 5000/account and flags `truncated:true`. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a connected bank: the totals/rows may be incomplete or wrong until the provider recovers, and reconnecting does not fix it.
    Connector
  • Returns CLOSED credit card bills for a CREDIT-type account: dueDate, totalAmount, minimumPaymentAmount, allowsInstallments, plus `payments[]` (id, paymentDate, amount, valueType, paymentMode), `payments_count`, `payments_total`, finance charges aggregates, and a derived `payment_status` per bill. IMPORTANT — Brazilian Open Finance semantics: Pluggy does NOT return a `paid`/`status` field. The payment goes into the `payments[]` of the bill whose CYCLE contains the paymentDate (closing ≈ dueDate − 7d): pre-payment before close stays on the bill being paid; payment between close and due, or after due, lands on the NEXT bill. So `payments[]` on a bill commonly carries the previous bill's payment, NOT the current one's — do NOT assume this bill was paid just because `payments[]` is non-empty. Use the derived `payment_status` (`PAID` | `OPEN` | `PAST_DUE_UNCONFIRMED` | `PAST_DUE_UNPAID`): a bill is `PAID` when its OWN `payments[]` (early pre-payment) or ANY newer bill in the payload contains a payment with amount ≈ this bill's `totalAmount` (±R$0.50). The MOST RECENT bill that's past-due, with no own pre-payment match, cannot be confirmed via cross-bill (the next cycle hasn't closed yet) — it returns `PAST_DUE_UNCONFIRMED`. NEVER call such a bill 'vencida' categorically; flag that the payment may have been made between close and due and not yet reflected upstream. The full `payment_status_legend` is returned alongside the results. OPEN BILL & TOTAL DEBT (standardized, derived — OPT-IN): pass `include_open_bill:true` to ALSO get `open_bill` (the current not-yet-closed bill, próxima a vencer) and `total_pending_debt` (saldo devedor total = all pending installments), BOTH derived from PENDING transactions so they mean the same thing across connectors — use these instead of the CREDIT account's `balance`, whose meaning VARIES by connector (some report the open-bill partial, others the full installment debt). `open_bill` = { available, method (`cycle_dates` = real close/due dates | `calendar_month_fallback` = estimated, `confidence:'low'`), close_date, due_date, total_amount (net charges − credits), transaction_count }; plus a `future_bills[]` breakdown per month — LOW-confidence forward projections of PENDING installments (`confidence:'low'`, `basis`), NOT authoritative bills (for closed months trust the `results` `totalAmount`). CONNECTOR ASYMMETRY: where the bank does NOT expose the open bill before closing (only closed bills, no reliable cycle dates), `open_bill.available` is `false` with a `reason` (`connector_exposes_no_pending` or `open_bill_not_published`) — that bill isn't retrievable by any endpoint until it closes (upstream limit of the institution's Open Finance feed, not our filter); check the bank app for the current open bill. When per-transaction billId grouping does not reconcile with the bills' totals, a `bill_grouping_reliability` warning is attached (trust `totalAmount`, do not sum by billId). Default `false` (the projection runs an extra accounts+transactions scan, so it's opt-in). The response opens with an `account` echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH card/bank these bills belong to. When more than one bank is connected, ALWAYS cross-check the echo against the card you intended to query and name the bank when presenting results — never attribute one bank's bills to another. This tool's `results` are bill-level summaries — NOT individual transactions, and each bill's `totalAmount` (from the bank) is the AUTHORITATIVE amount. To see itemized purchases/charges, use openfinance_list_transactions with the CREDIT account_id — but note `creditCardMetadata.billId` is a per-connector hint that can be sparse/inconsistent (e.g. Nubank), so do NOT reconstruct a bill total by summing transactions by billId. Returns a warning instead of failing if the CREDIT_CARDS product is not enabled. Bulk support: accepts account_ids for batched execution.
    Connector
  • Forces the bank to re-sync one or more connections NOW and WAITS for it to finish (PATCH /items/:id, then polls until the item stops updating, up to ~60s). Use this when a balance or transaction list looks stale: a connection can read UPDATED yet be hours old, and this pulls fresh data WITHOUT disconnecting/reconnecting. Pass `items` as an array of selectors (item_id, connector_id, or connector_name); OMIT `items` to sync ALL linked banks. Returns `{ results, errors }`; each result has the final `status`, `executionStatus`, `lastUpdatedAt` (advances when data is refreshed), and `synced` (true = fresh data is ready). `needs_action` (e.g. MFA_REINTERACTION / LOGIN_ERROR / WAITING_USER_INPUT) means the user must re-authenticate — those results include a `reconnect_url` that opens the widget in UPDATE mode for that exact connection (user enters credentials / MFA token, data refreshes in place, no slot consumed, no disconnect needed). `timed_out: true` means the sync is still running — re-check with openfinance_get_item_status. Set `wait: false` for fire-and-forget (returns immediately while UPDATING).
    Connector
  • Returns bill-level detail for one or more credit card bills by id (GET /bills/:id): financeCharges and payments[] (id, paymentDate, amount, valueType, paymentMode). Does NOT return individual transactions — to get itemized credit card transactions (purchases, subscriptions, etc.), use openfinance_list_transactions with the credit card account_id and a from/to date range matching the bill's billing cycle (approximately dueDate − 30d to dueDate); each transaction MAY carry a `creditCardMetadata.billId` hint toward its bill, but it's sparse/inconsistent on some connectors (e.g. Nubank), so do NOT reconstruct a bill total by summing transactions by billId — the bill's own `totalAmount` is authoritative. Pass `bill_ids` as an array — use openfinance_list_credit_card_bills first to discover ids. `{ results, errors }` batch shape. NOTE: Pluggy does NOT return a paid/status field. In Brazilian Open Finance, `payments[]` reflects payments registered during THIS bill's billing cycle — typically the payment of the PREVIOUS bill (do NOT assume this bill was paid just because `payments[]` is non-empty). To check paid status, prefer `openfinance_list_credit_card_bills` which derives `payment_status` via cross-bill match.
    Connector
  • Fetch one X account's profile: name, bio, location, website, follower/following counts, tweet and media counts, verification state, and join date. identifier accepts a screen name without the @ (e.g. 'nasa'), a full x.com or twitter.com profile URL, or the numeric account id; numeric strings are treated as ids, and the rare all-digit handle can be forced with by='screen_name'. Costs 4 credits. The returned platform_fields.id is stable across handle changes; store it for repeat lookups. To find accounts by topic use x_search type=people, and to read what an account posts use x_get_tweets; this tool returns no tweets.
    Connector
  • Fetch one page of an X account's timeline. identifier is a screen name, profile URL, or numeric id (auto-detected). mode picks the view: posts (default) is the account's own tweets, posts_and_replies includes their replies, highlights is the account's pinned highlights tab. include_retweets (default true) filters retweets out when false. Costs 4 credits per page; a cursor page is a NEW call priced the same way. Returns tweet summaries with engagement counts and a cursor for older tweets. Use this for 'what has X been posting', voice checks before outreach, or drafting replies in an account's register. For keyword search across all of X use x_search; for one specific tweet you already have, x_get_tweet.
    Connector