What can you do with IronClaw?

On first run the agent asks the user: (1) the niche to filter on — defined as any combination of keywords (e.g. "NEAR Protocol", "Rust async", "AI agent frameworks", "WooCommerce"), topics or categories (crypto, dev tools, AI, fintech, gaming, ecommerce, etc.), source handles or feeds to anchor on, and any negative keywords to exclude (e.g. "no memecoin drama", "no NFT shilling"). (2) Which sources to pull from — any combination of RSS feeds (any URLs the user pastes), Hacker News (top stories, best, new, show, ask, with optional keyword filter), and Reddit (any subreddits the user picks, with optional keyword filter). (3) The filter mode — strict (only items that directly match the niche keywords or topics), balanced (direct matches plus AI-semantic-similar items — this is the default and is recommended for most users), or exploratory (broader than the niche, surfaces adjacent topics the user might want to discover). (4) The delivery channel — Slack, Notion (written to a database the agent sets up with fields: title, source, summary, link, niche tag, why-it-matters line, posted date), Telegram, or email — the user picks exactly one. (5) The send time and the user's timezone (no default, the user must pick). These preferences are stored. On every fire the agent pulls the last 24 hours of activity from each enabled source (RSS "New Feed Item", Hacker News "Top Stories" + keyword search, Reddit "New Posts" in the picked subreddits + keyword search), runs the user's filter mode against the raw stream, ranks the surviving items by a combination of source weight, recency, and AI confidence that the item matters to the user's niche, and produces a tight digest of 3 to 7 items. Each item carries: the source label (e.g. "Hacker News — front page", "RSS — Stratechery", "Reddit — r/programming"), a 1-line summary, the original link, the matched niche tag, and a 1-line "why this matters for you" written for the user's specific niche. The digest opens with a 2–4 line TL;DR capturing the dominant themes of the day across all sources, then the item list. The whole thing is delivered to the chosen channel (Slack "Send Channel Message", Notion "Create Database Item" per row + a single summary message, Telegram "Send Message", or Gmail "Send Email"). The user can at any time ask the agent for an on-demand view ("show me this week's crypto items only", "what was the top AI story today", "expand on the third item"), re-rank the niche weight (boost or mute a keyword), add or remove a source, switch the filter mode, or change the delivery channel.

On first run the agent asks the user: (1) the domains to monitor — work, personal, and / or family (any combination), (2) the user's top goals in each enabled domain (e.g. work — "ship faster and reduce meetings"; personal — "sleep more and read more"; family — "less meal-prep chaos"), and (3) which mode the agent should run in — propose-only (agent suggests, the user approves, the agent sets up) or propose + auto-build (for low-risk simple workflows the agent sets up directly and notifies the user with a one-liner "I created X, say stop to disable"). These preferences are stored. The agent runs a weekly scheduled review (the user picks the day and time — Sunday evening is a common default) on a cron-like cadence, and in every review it scans the last 7 days of activity across the user's interactions with the agent and across any connected sources the user has authorized (Gmail, calendar, task apps, expense log, family shared calendar, etc.). It looks for four classes of signal: (a) repeated user requests — the same task requested three or more times in the period, even if worded differently; (b) time-based patterns — "every weekday at 8am the user asks for an email digest", "every Sunday the user manually reviews receipts"; (c) cross-use-case connections — the user is using the invoice digest and the receipt capture separately, and a unified expense view would save time; (d) goal-based gaps — the user's stated goal of "sleep more" has no workflow attached, so the agent proposes a wind-down reminder or screen-time tracker. Each finding is packaged into a short weekly recap the user gets in their primary channel (Slack, Telegram, or email — whichever they picked) with: a one-line observation per pattern, a one-line proposed automation, an estimated time saved per week, an effort / risk tag (low / medium / high), and a clear "approve / skip / modify" call to action. In propose-only mode the agent waits for approval before doing anything. In propose + auto-build mode the agent builds any low-risk simple workflow directly and notifies the user with a one-liner plus an easy way to disable. The agent can also be asked on demand at any time ("what patterns did you see this month", "what would you suggest for my work week", "any new automations you would build for the family"). The agent never modifies high-risk or destructive workflows (anything that sends money, deletes data, or messages third parties on the user's behalf) without explicit per-instance approval.

On first run the agent builds a family profile by asking the user: (1) who is in the family — names, roles (adult / child / elderly), and the channel each person uses for notifications (one channel per person, picked from Slack, Telegram, or email). (2) For reminders: the user adds a shared family calendar of recurring and one-off items — anniversaries, school events, medication times, recurring chores, bill due dates — and can also set context-aware reminders that fire on a condition (e.g. "remind me to buy milk when the receipt shows fewer than 2 cartons left this week", wired into the invoice-stream use case, or "remind the kids to do homework every weekday at 4pm"). Reminders are family-shared by default — anything marked shared shows up in a single family channel plus each member's individual channel; anything marked private goes only to the owner. (3) For the meal planner: the agent creates a per-member profile with dietary needs (vegan, halal, kosher, allergies, low-sodium, etc.), taste preferences (spicy / mild / sweet, favorite cuisines, dislikes), and any notes (e.g. "picky eater, will not eat fish"). On a weekly cadence (user picks the day and time) the agent generates a 7-day meal plan with breakfast / lunch / dinner for each family member, respects all dietary constraints, reuses what is already in the fridge when possible (cross-references recent grocery receipts from the invoice / receipt use cases), and balances variety week over week. The plan is delivered to the family's shared channel and to each member's individual channel. From the plan the agent auto-builds a shopping list grouped by aisle / category and sends it to the channel the user picks. The user can give feedback after any meal ("kid refused the fish tonight" / "spice level was perfect for me") and the agent updates each profile's taste model so future plans get more accurate. (4) For the bedtime story generator: the agent keeps a per-child profile (name, age, favorite characters, themes like "dragons and kindness", preferred length — short ~5 min or longer ~15 min, any fears to avoid). Every night at the user-set bedtime the agent generates a fresh, original bedtime story tailored to that child and sends it to the parent's channel. Sibling story series are supported — the agent can keep a continuing storyline across nights if the parent wants. Output is text returned in chat, and a notification is pushed to the channel the parent picks (Slack, Telegram, or email) so the parent can read it aloud or forward it. The agent learns over time from feedback ("too scary", "loved the talking turtle — more animals like that", "shorter tonight, she's tired") and quietly tightens its generation per child. Across all three sub-domains the agent is proactive — it pushes the meal plan and shopping list on schedule, fires recurring and context-aware reminders, and delivers the bedtime story without being asked — and the user can talk to it any time to adjust plans, add or remove a family member, or change a profile.

On first run the agent asks the user: (1) the Telegram account to use — the user authenticates a user-account session via MTProto (the agent explicitly warns the user that Telegram's TOS restricts user bots, that accounts can be banned for abuse, and that the user is responsible for complying with Telegram's rules and with the rules of any group they monitor). The user picks the read-only scope: the agent will view messages, view members, and view reactions, and will not auto-post, auto-translate, auto-join, auto-leave, or auto-reply on the user's behalf. (2) Which groups to monitor — the user pastes group identifiers or picks from a list of groups the account is already in. The user can pick any number, and can drop or add groups at any time. (3) The keyword and filter set — the user provides a list of keywords / phrases to watch (brand name, product names, common issue words, language variants), a list of negative keywords to exclude noise, and optional filters by sender, time-of-day, or whether the message contains a question mark or is at least N characters long. (4) The categorization labels the agent should apply to each match — the agent suggests a default (bug report, feature request, general question, appreciation, spam) and the user can replace or extend the list. (5) Cadence and delivery for the recap and the cross-group digest (daily or weekly; per-group or rolled-up into one digest; sent to the user's Telegram DM, Slack, or email — user picks one). (6) Reminder rules — the user picks the unanswered-mention threshold (e.g. "remind me if a question from a non-team member has no reply from any team member after 4 hours"), the engagement threshold (e.g. "flag a post if it crosses 10 reactions and is more than 6 hours old and is not pinned"), and the destination for reminders (Telegram DM, Slack, or email). These preferences are stored. The agent runs on a polling cadence (the user picks, default every 5-15 minutes) and on every fire reads new messages from each monitored group via the MTProto session, runs the keyword and filter set, applies the categorization labels, and updates a per-group rolling state. When a match lands, the agent pushes a short notification (sender, group, message excerpt, category, link) to the chosen channel if the message is high-signal (e.g. matches a priority keyword, comes from a frequent contributor, or contains a clear question). At the user's chosen recap time, the agent generates a per-group recap of the last 24h (or 7 days) with: the top 3-5 threads, a one-line sentiment summary, the most-asked questions, and a list of items still awaiting a reply, and a cross-group digest that surfaces topics appearing in two or more monitored groups in the same period ("topic X is trending in 5 groups"). Reminders fire on the user's rules — unanswered mention, low-engagement high-potential post, brand mention without a team response, or any other rule the user configures. The agent never auto-sends anything back to any group; every notification is read-only and delivered only to the user's chosen private channel. The user can at any time ask the agent for an on-demand recap, refine keywords, add or remove a group, tighten or loosen a reminder rule, or pause the monitor entirely. Hard constraints: the agent is read-only and MUST NOT auto-post, auto-translate, auto-join, auto-leave, or auto-reply on the user's behalf in any monitored group. Every output is observational and delivered only to the user's chosen private channel. The user is responsible for complying with Telegram's TOS, which restricts user bots and can result in account bans for abuse.

On first run the agent asks the user: (1) the Telegram account to use — the user authenticates a user-account session via MTProto (the agent explicitly warns the user that Telegram's TOS restricts user bots, that accounts can be banned for abuse, and that the user is responsible for complying with Telegram's rules). The user picks a read-only scope: the agent will view messages, view contact profiles, view chat history, and log a daily summary; it will not draft replies, not auto-reply, not auto-add contacts, not auto-join groups, not cross-post, and will not download or persist any attachment (no PDF, no image, no audio, no video — the attachment rule is a hard constraint and is enforced at the MTProto client level). (2) Volume tier — low (under 10 DMs / day, single morning recap), medium (10-50 DMs / day, single morning recap plus an optional mid-day check), or high (50+ DMs / day, two recaps per day plus per-thread summarization). Default is medium. (3) Recap cadence and delivery — daily recap time + timezone (no default; the user must pick), and the delivery channel (Telegram DM back to the same user bot account is the default, with Slack and email as alternatives). (4) Where to store the contact log — the default is a local Markdown file per day at a path the user picks (e.g. ~/telegram-recap/contacts-YYYY-MM-DD.md), and the agent mirrors the same file as a message into the user's Telegram Saved Messages so the log is always retrievable from the phone. The user can switch to Notion (database with fields: contact handle, contact name, last interaction, summary, needs-reply flag, link to thread), Google Contacts (sync to a labeled group), or Airtable. (5) Priority grouping rules for the recap — the agent suggests a default (needs-reply if the last message in the thread is from the other party and contains a question, an ask, or a clear call to action; FYI if the message is informational with no question; can-skip for automated notifications, opt-in marketing, or anything the user has previously muted), and the user can refine the rules. These preferences are stored. On every fire the agent reads the last 24 hours of incoming DMs to the user bot account via the MTProto session, applies the priority grouping rules, and produces a tight 5-minute recap with: a one-line headline ("today: 23 DMs, 5 need a reply, 3 FYI, 15 noise"), a needs-reply section listing each contact with a 1-3 line summary of what they want, a FYI section with the same per-contact format, and a single one-line "noise" count rather than a list. The recap is delivered to the chosen channel. At the same time the agent appends a per-day Markdown entry to the local contact log file, with one section per contact that has had any interaction in the window (handle, name, last message excerpt, summary, link to the Telegram thread, priority group). The file is then mirrored as a single message into the user's Saved Messages (or sent to the chosen destination). The agent never downloads or saves any attachment — if a contact sent a file, the recap line for that contact notes "attachment sent (not downloaded)" so the user knows to look in the original thread, and the agent does not retain a copy. The user can at any time ask the agent for an on-demand view ("recap my DMs from the last 6 hours", "give me the full thread with Alice from this week", "what did Bob say about the Series A"), change the volume tier, refine priority rules, switch storage destination, or pause the recap entirely. Hard constraints: (1) No attachment downloads — the agent MUST NOT download, save, mirror, OCR, transcribe, or otherwise persist any file attachment (image, PDF, audio, video, voice message, sticker, document); this is enforced at the MTProto client level, and if a contact sends a file the recap notes "attachment sent (not downloaded)" and the user is expected to look in the original thread. (2) Read-only — the agent MUST NOT draft a reply, send a message, add a contact, join a group, leave a group, or cross-post to a channel on the user's behalf; every output is observational and the user reads the recap and acts manually.

You tell the agent your goals and deadlines once. Every morning at 9 AM it reads your goal list from memory, checks how long ago you last updated each goal and how close the deadline is. If you haven't logged any progress in 3+ days it flags the goal as STUCK. If the deadline is 2 days away or less it flags as URGENT. You only get a Telegram message when something actually needs your attention — silent run otherwise. Update your progress anytime by texting the agent, and it updates the memory file.

On first run the agent asks the user: (1) which sources to aggregate — any combination of Gmail, Google Calendar, Slack, Telegram, task apps (Todoist / Trello / Notion / Asana), and GitHub, with the understanding that the user can add more sources later through additional MCPs or Zapier connections without rewriting the use case. (2) The default working hours for the time-blocked view (e.g. 6:00 AM to 10:00 PM) and the user's preferred daypart blocks (focus block, meeting block, admin block, family / personal block) — the user can keep the agent's defaults or define their own. (3) Cadence — the agent runs the schedule build twice a day: a night-before preview (default 9:00 PM, user picks) and a same-morning finalization (default 6:30 AM, user picks). (4) Calendar event creation mode — propose (the agent shows the proposed event and asks for one-tap approval before creating), auto (the agent creates the event directly when the commitment is high-confidence and the time slot is open, and asks only on conflict), or skip (the agent lists commitments in the schedule view but never touches the calendar). (5) Delivery channel for the schedule (Slack, Telegram, or email — single channel). These preferences are stored. On every fire the agent pulls the next 24 hours of activity from each enabled source: Gmail (search for date / time / "tomorrow" / "let's meet" / "by " mentions plus the user's starred items), Google Calendar (existing events as the schedule anchor), Slack and Telegram (recent messages containing commitments or deadlines), task apps (items due tomorrow or with no due date but recent activity), and GitHub (PR review requests, issue milestones, release dates). The agent runs a single AI pass that (a) extracts every commitment with a time or deadline, (b) anchors them to the existing calendar, (c) fills the gaps between fixed events with the user's configured blocks (focus, admin, personal), (d) detects conflicts (two meetings at the same time, or a task deadline that collides with a fixed event), and (e) flags anything that needs the user's attention. The output is a time-blocked daily schedule with: a one-line TL;DR on top ("3 meetings, 2 deadlines, 1 conflict"), a chronological list of fixed events pulled from the calendar, a list of extracted commitments with their source (e.g. "Gmail — John asked to sync at 3 PM"), the proposed / auto-created / skipped calendar events for those commitments per the user's mode, a conflict section, and the proposed focus / admin / personal blocks for the gaps. The agent always asks before creating a calendar event on the user's behalf (in propose mode this is explicit, in auto mode only on conflict). In the morning fire the agent re-pulls sources to catch anything that landed overnight, refreshes the schedule, and sends a finalized version to the same channel. The user can at any time ask the agent for an on-demand rebuild ("rebuild my schedule", "what's left for the rest of today", "show me next week's commitments across all sources"), change the working hours, add or remove a source, or switch the calendar-creation mode.

Help in day to day work like Chatgpt. Research, documentation, searchm summarize.

The agent reviews your calendar, task lists, deadlines, and ongoing projects. It creates a structured weekly plan, identifies scheduling conflicts, allocates focus time, and recommends adjustments to improve productivity.

The agent researches shows, compares themes, reviews audience feedback, filters based on your requirements, and delivers a shortlist with detailed explanations.

On first run the agent asks the user: (1) which sources to accept — Gmail (Zapier or native trigger on incoming mail matching receipt keywords), photo upload (the user can send a receipt photo to the agent via Telegram, Slack, or email and the agent OCRs it), and manual entry (the user forwards or pastes raw text). The user can enable any combination. (2) Where to store expenses. The default is Google Sheets because it is the most common choice for freelancers and small business owners and exports cleanly into any tax tool. The agent also suggests Notion (database) and Airtable as alternatives — if the user picks one of those, the agent connects it through Zapier MCP, Make.com, or Composio, whichever the user already has or prefers. (3) The category list to use (default: software / subscriptions / travel / meals / utilities / office / other — fully user-replaceable). (4) How strict the "deductible" flag should be — strict (only flag when the AI is highly confident), lenient (flag by default, user un-checks false positives), or off entirely. These preferences are stored. On every new receipt from any enabled source the agent runs AI extraction to produce: merchant, date, amount, currency, tax, category, payment method, free-text notes, and the deductible flag. It then appends a new row to the chosen storage (Google Sheets via Zapier "Create Spreadsheet Row" or native, Notion "Create Database Item" via Zapier / Make.com / Composio, or Airtable "Create Record" via Zapier). For photo receipts the agent also keeps a link to the original image alongside the row. The user can at any time ask the agent for an on-demand view ("what did I spend on travel this month", "show me all deductible expenses for Q1", "total tax I paid on software last 90 days"), change categories, switch storage destination, or trigger an export ("send me a CSV of all expenses this year", "give me a tax-ready summary grouped by deductible category"). The agent also supports a quarterly nudge: at the end of each quarter it sends a one-line reminder with the quarter's deductible total so the user can plan ahead for tax season.

Continuously monitors live prices, market cap changes, and chain-level supply distribution for the configured stablecoins. If any coin dips below the set threshold — or if the agent detects sudden supply drops, liquidity drains, or breaking news about the issuing protocol — it fires an urgent alert explaining exactly what happened, which chain it's on, and whether you should investigate or act. It also checks recent news for protocol incidents that could precede a depeg event.

On first run it asks the user which symbols to track in their watchlist (default BTC, user can add ETH, NEAR, etc.), which mode they want (on-demand only, scheduled alerts only, or both), and what alert threshold they care about (e.g. only STRONG BUY / STRONG SELL, or any non-neutral verdict). It stores those preferences. In on-demand mode, the user can ping the agent with any symbol and timeframe and gets a weighted multi-timeframe technical analysis with a clear verdict, suggested entry, stop loss, and take-profit, plus the indicators that drove the call. In scheduled mode, the agent runs on a routine, scans the user's watchlist, and pushes a short alert to the user's default output channel whenever a verdict crosses the configured threshold. The output is written so a trader can act on it in under a minute.

The agent fetches the 25 most recent Bitcoin-related posts from r/cryptocurrency using the public RSS feed (no API key required). It parses each post's title and description, classifies sentiment as positive, negative, or neutral based on keywords and context, then counts the breakdown. If positive posts outnumber negative by 5+, it labels the mood BULLISH; if negative dominates, BEARISH; otherwise MIXED. It sends a clean Telegram summary with the counts, overall label, and the most interesting signal post it found.