ljang0/MyPCBench-tasks huggingface dataset:
Task (hard, situated_action / bounded_action)
Primary app: kwik_e_mart
Apps involved: Kwik-E-Mart

Instruction: Reorder my last run from a Kwik-E-Mart store I've used recently — pick a store I've ordered from most often OR most recently in my order history. If anything's out of stock, swap in reasonable substitutes (otherwise just keep what's available). Do a quick price check against another store in the app so I know I'm not getting fleeced, and schedule delivery for before end of day today.

Grading criteria:
criterion: Agent opens Kwik-E-Mart and navigates to the order history view to surface a prior run at one of Michael's top-frequency stores or his most-recent store
criterion: Agent picks a reorder anchor at one of Michael's top-frequency Kwik-E-Mart stores by order count (any store tied at the top by order count is acceptable) OR his most-recent Kwik-E-Mart order, and bases the reorder on that order's line items
criterion: Agent starts a reorder and handles out-of-stock items appropriately — picks substitutions if any items are flagged OOS, or notes that all original items were available and proceeds without substitutions
criterion: Agent opens a second store and compares prices
criterion: Agent completes the price comparison and proceeds with the cheaper option (returns to the original store's cart if it is cheapest, or switches to the cheaper store)
criterion: Agent selects the earliest available delivery slot at Kwik-E-Mart checkout for the chosen-store reorder
criterion: Agent places the Kwik-E-Mart reorder and verifies it appears in the recent-orders history after checkout
Task (hard, long_horizon / bounded_action)
Primary app: kwik_e_mart
Apps involved: Kwik-E-Mart

Instruction: Build me a Kwik-E-Mart shopping spree for Dundies catering for about a hundred people: drinks, chips, plates, plastic silverware, napkins, plenty of ice, the works. Use Wegman's. Check out with delivery to my home address and make sure the delivery window is at least a two-hour slot so I'm not stuck waiting by the door all afternoon.

Grading criteria:
criterion: Agent opens Kwik-E-Mart, selects Wegman's as the store for the Dundies catering bulk order (instruction explicitly specifies Wegman's), and views any existing shopping lists before building the new catering list
criterion: Agent creates or extends a Dundies Catering shopping list (or a 'Party Supplies' list) in Kwik-E-Mart for the catering items
criterion: Agent adds 6+ Kwik-E-Mart shopping list categories (drinks, chips, plates, plastic silverware, napkins, ice) with quantities scaled for 100 people
criterion: Agent moves the Dundies Catering Kwik-E-Mart shopping list contents into the cart
criterion: Agent confirms delivery address is 1725 Slough Ave (Michael's home address) at Kwik-E-Mart checkout
criterion: Agent picks a delivery window at least 2 hours wide at Kwik-E-Mart checkout so Michael is not waiting all afternoon
criterion: Agent places the Kwik-E-Mart Dundies catering order and confirms the order total and delivery window persist in order history
criterion: Agent verifies the Dundies Catering shopping list persists and displays in Kwik-E-Mart shopping_lists after checkout
Task (easy, preference_inference / pattern_inference)
Primary app: kwik_e_mart
Apps involved: Kwik-E-Mart

Instruction: What's my favorite grocery store, and what do I actually buy there? Rank my stores and give me a quick profile of my shopping habits in LibreOffice Writer. 

Grading criteria:
criterion: Agent identifies Michael's favorite Kwik-E-Mart grocery store as the top-by-order-count store from live order history (/api/orders), naming whichever store has the plurality of orders
criterion: Agent reports the live order counts per store from Michael's Kwik-E-Mart order history (/api/orders), confirming the top-by-order-count store is ranked first ahead of the other stores Michael has used
criterion: Agent characterizes the typical line items Michael buys there
criterion: Agent writes a one-paragraph profile of Michael's Kwik-E-Mart grocery shopping habits at his favorite store
criterion: Agent reads Kwik-E-Mart order-history line items and states them as the data source backing the favorite grocery store ranking and buying profile
criterion: Agent delivers the favorite Kwik-E-Mart grocery store ranking and the buying-habits profile before ending the task
Task (hard, situated_action / bounded_action)
Primary app: kwik_e_mart
Apps involved: Kwik-E-Mart

Instruction: I need groceries from Price Chopper this week (changing it up from Wegmans). Reorder whatever I got the most recent time I shopped at Price Chopper on Kwik-E-Mart and have it delivered to home. Tip 20%, I feel bad for not tipping last time. Make sure we add oat milk and eggs if not in the order, need those!

Grading criteria:
criterion: Agent opens Kwik-E-Mart and locates Michael's most-recent Price Chopper order in the order history (filtering by store and picking the most recent Price Chopper basket as the anchor)
criterion: Agent copies the line items from that Price Chopper order into the new reorder cart at Price Chopper (not Wegmans or another store)
criterion: Agent adds oat milk to the cart if it was not already in the Price Chopper reorder, and adds eggs if they were not already in the Price Chopper reorder, per Michael's explicit request
criterion: Agent sets a 20% tip on the Kwik-E-Mart Price Chopper order at checkout
criterion: Agent selects Michael's home address (1725 Slough Ave, Apt 4B) as the Kwik-E-Mart delivery destination and submits the Price Chopper reorder checkout
Task (medium, situated_action / bounded_action)
Primary app: libreoffice
Apps involved: LibreOffice Writer

Instruction: Open my Dundies 2026 categories doc in Writer, bold the 'Whitest Sneakers' line, then add a new category called 'Fine Work Outfit' right after it. Save it when you're done.

Grading criteria:
criterion: Agent opens LibreOffice Writer before loading the Dundies 2026 categories document for the bold and append edits
criterion: Agent opens the Dundies_2026_Categories.txt file in LibreOffice Writer (not a terminal editor)
criterion: Agent finds the 'Whitest Sneakers' line in the Dundies 2026 categories doc and selects it before applying formatting
criterion: Agent applies bold formatting to the 'Whitest Sneakers' line during the editing session via Ctrl+B or the toolbar bold button (visible in screenshots; bold attribute will not persist when the .txt source file is saved back as plain text — accept screenshot evidence of the formatting being applied at any point in the session)
criterion: Agent inserts a new 'Fine Work Outfit' category line immediately after the 'Whitest Sneakers' line in the Dundies 2026 categories doc
criterion: Agent saves the edited Dundies_2026_Categories.txt file back to the same ~/Documents path in Writer, keeping the original text format if prompted
Task (hard, long_horizon / bounded_action)
Primary app: libreoffice
Apps involved: LibreOffice Writer

Instruction: Write me a one-page Dundies 2026 invitation in Writer. I want a big bold title at the top, a bulleted list of this year's categories pulled from my Dundies categories doc, and a signature block that says 'Michael Scott, World's Best Boss'. Save it to my desktop so I can print a stack.

Grading criteria:
criterion: Agent reads ~/Documents/Dundies_2026_Categories.txt to retrieve this year's Dundies category names for the invitation
criterion: Agent opens LibreOffice Writer and creates a new document for the Dundies 2026 invitation
criterion: Agent writes a big bold centered top-of-page title reading 'THE DUNDIES 2026' in the Writer invitation document
criterion: Agent writes a short Dundies 2026 invitation intro paragraph below the title in the Writer document
criterion: Agent inserts a bulleted list of this year's Dundies categories pulled from Dundies_2026_Categories.txt into the Writer invitation document
criterion: Agent adds a signature block reading 'Michael Scott, World's Best Boss' at the bottom of the Writer invitation document
criterion: Agent saves the Dundies 2026 invitation as ~/Desktop/dundies_invite.odt fitting on a single page
Task (medium, long_horizon / multi_step_orchestration)
Primary app: libreoffice
Apps involved: LibreOffice Impress
Dinoco Airlines
Cheskepdia
HooliMail

Instruction: Throw together a three-slide Impress deck for my Jamaica trip: one slide for the flight info, one for the Sandals hotel info, and one with a rough daily schedule. Save it into my Trips documents folder.

Grading criteria:
criterion: Agent creates an Impress deck for Michael's Jamaica trip that contains exactly 3 slides (flight, hotel, daily schedule)
criterion: Agent writes the Jamaica trip flight slide showing the flight number, departure time, confirmation code, and fare, all pulled from Michael's live Dinoco and/or HooliMail Jamaica trip sources (not invented)
criterion: Agent writes the Sandals hotel slide showing Sandals Montego Bay, the live Cheskepdia confirmation number, the live check-in and check-out dates, and the live total price — all read from Michael's Cheskepdia booking
criterion: Agent writes the third Jamaica trip slide as a rough day-by-day schedule spanning the live Sandals Montego Bay check-in/check-out window
criterion: Agent saves the three-slide Jamaica trip Impress deck to ~/Documents/Trips/jamaica_itinerary.odp inside Michael's Trips documents folder
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: HooliMail
HooliCalendar
HooliChat
HooliWork
Gringotts

Instruction: It's early morning today. Give me a morning brief in LibreOffice Writer covering any priority email from this week, what's on my calendar today, anything that came in overnight on HooliChat or HooliWork, and any charges that hit my card since midnight.

Grading criteria:
criterion: Agent surfaces important or unread HooliMail messages from the current week using 'from sender' or 'this week' framing (heuristic priority flagging by sender/subject is acceptable when no explicit priority/star flag is set)
criterion: Agent enumerates today's HooliCalendar events by reading the UI
criterion: Agent checks HooliChat and HooliWork for overnight messages and summarizes them
criterion: Agent reviews Gringotts for transactions posted since today's midnight
criterion: Agent delivers a consolidated morning brief that covers HooliMail priority email, HooliCalendar events, HooliChat/HooliWork overnight messages, and Gringotts charges
criterion: Agent organizes the morning brief so the four sources (email, calendar, overnight HooliChat/HooliWork, Gringotts card charges) are each clearly distinguishable and scannable
criterion: Agent includes all four morning-brief sources (HooliMail, HooliCalendar, HooliChat/HooliWork, Gringotts charges) before ending the task
Task (medium, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: Cheskepdia
Gringotts

Instruction: What did that recent Philadelphia overnight trip cost me all-in? It was a quick one-night hotel stay downtown. Give me the damage from the hotel and any related card charges.

Grading criteria:
criterion: Agent opens Cheskepdia and reads the live Philadelphia overnight hotel booking (property name as shown on the Cheskepdia booking record), reporting its total price and dates as shown live
criterion: Agent cross-references Gringotts around the Philadelphia overnight trip dates (as read from the Cheskepdia booking) for related card charges such as the hotel (the hotel charge on the card may appear under a different merchant name — e.g. Hilton Garden Inn — than the Cheskepdia booking property, and may post on or shortly after the checkout date), gas, or food
criterion: Agent reports the combined Philadelphia trip total (hotel + any on-trip card charges) as the all-in damage Michael asked for
criterion: Agent states the Philadelphia trip all-in damage as a single final dollar figure combining the hotel and incidentals (not assuming a flight)
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: Cheskepdia
Dinoco Airlines
Gringotts

Instruction: Add up what I've already committed to the Barbados trip in a LibreOffice Calc sheet and flag any gap. I know the hotel is booked but I'm not sure if the flight charge actually hit yet.

Grading criteria:
criterion: Agent reads the Sandals Royal Barbados hotel booking total from Cheskepdia to add up Michael's committed Barbados trip spend
criterion: Agent locates Michael's Barbados flight booking on Dinoco Airlines and notes its confirmation code
criterion: Agent identifies the Dinoco Airlines Barbados flight charge in Gringotts (matching by confirmation code DN-78558 or the AVP->BGI route) as a charge that has posted to the account
criterion: Agent identifies the Cheskepdia Sandals Royal Barbados hotel charge in Gringotts as a charge that has posted to the account
criterion: Agent computes the total committed Barbados trip spend by summing the posted Gringotts charges (flight and hotel) and correctly represents what has actually been charged to the card
criterion: Agent enters the committed trip totals into a LibreOffice Calc sheet and flags any remaining gap (such as incidentals or future charges not yet posted)
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: SprintBoard
HooliWork
HooliCalendar
Files

Instruction: Build me a standup summary for today covering all the open issues on SprintBoard, what I posted on HooliWork, and what meetings I have including the takeaways from the recent all-hands (notes are saved on my Desktop as meeting_notes_allhands).

Grading criteria:
criterion: Agent enumerates all open SprintBoard issues across Michael's active projects (if none, reports 'no open issues' rather than fabricating)
criterion: Agent reports Michael's HooliWork posts (if none, reports 'no posts' rather than fabricating)
criterion: Agent reads Michael's HooliCalendar meetings visually from the UI and includes them in the standup summary
criterion: Agent assembles Michael's standup summary so the three topics (SprintBoard open issues, HooliWork posts, HooliCalendar meetings) are each clearly distinguishable (using 'none' where applicable)
criterion: Agent writes the standup summary as plain-text bullets that Michael can paste directly into a HooliWork channel to sound prepared
criterion: Agent actually checks all three standup sources (SprintBoard open issues, HooliWork posts, HooliCalendar meetings) before assembling the summary, even if some are empty
criterion: Agent opens ~/Desktop/meeting_notes_allhands.txt and includes the takeaways in the standup summary (not just the meeting title)
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: HooliShop
HooliChat
Files
LibreOffice Calc
LibreOffice Writer

Instruction: Pull together everything I've spent or committed to the Dundies this year so far into a LibreOffice Calc Spreadsheet. Check my trophy orders, any mentions in the planning group chat, and the categories doc. Write up a report in LibreOffice Writer when you're done.

Grading criteria:
criterion: Agent searches HooliShop for any current-year trophy/award orders tied to the Dundies, reading the grand total if found and noting absence if none exists
criterion: Agent scans HooliChat 'Dundie Awards Planning' group for any referenced costs
criterion: Agent reads the Dundies 2026 categories doc (Documents/Dundies_2026_Categories.txt) in Files for any cost references
criterion: Agent produces a clear Dundies budget rollup entered into a LibreOffice Calc spreadsheet
criterion: Agent labels each Dundies cost line as known vs. unknown in the rollup and marks anything not yet committed (including the trophy line if no order exists)
criterion: Agent checks all three Dundies sources (HooliShop for trophy/award orders, HooliChat 'Dundie Awards Planning' group, Dundies categories doc) before producing the rollup
criterion: Agent writes a summary report in LibreOffice Writer (separate from the Calc spreadsheet) covering the Dundies budget findings
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: SprintBoard
HooliWork
LockedIn
HooliMail
Files
LibreOffice Impress

Instruction: Put together a last-quarter performance review packet I can send to David Wallace. Pull my project progress (closed and open), my chat participation, any LockedIn posts, and relevant sent email threads. Pair it with a quick forward-look using the quarter sales forecast doc in ~/Downloads/ so David sees I'm thinking next quarter too. Make me look good. Build the actual perf-review packet as a LibreOffice Impress 4-slide deck (project progress / chat + LockedIn presence / forward-look / ask) — David likes visuals.

Grading criteria:
criterion: Agent summarizes last-quarter SprintBoard project progress across Michael's projects, covering both closed (completed) and open (in-progress) tasks for each project
criterion: Agent reports HooliWork participation by top channels for the last completed quarter
criterion: Agent reads LockedIn for last-quarter post count and engagement (even if only 1 post or zero, agent reports the live count and any engagement metrics for that post)
criterion: Agent references Michael's sent mail threads from the live HooliMail Sent folder for last-quarter topics (reading whatever From: address the seeded sent messages actually use)
criterion: Agent delivers a coherent last-completed-quarter performance review packet addressed to David Wallace pulling project progress, chat participation, LockedIn posts, and sent email threads
criterion: Agent organizes the performance review packet so each of the four sources (SprintBoard projects, HooliWork chat, LockedIn posts, HooliMail threads) is clearly represented and cites specific numbers
criterion: Agent checks all four last-quarter performance review sources (SprintBoard, HooliWork, LockedIn, HooliMail) before assembling the packet for David Wallace
criterion: Agent reads ~/Downloads/DunderMifflin_Q2_Sales_Forecast.txt and folds a forward-look paragraph from it into the last-quarter perf-review packet
criterion: Agent builds the last-quarter perf-review packet as a LibreOffice Impress 4-slide deck (one slide each: project progress / chat + LockedIn presence / forward-look from the sales forecast doc / explicit ask)
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: SpeedTax
Files
Gringotts

Instruction: Roll up my tax deductions for my accountant. Pull the line items (charitable, home-office days, 1099 income, W-2 gross/withholdings) from my in-progress Tax Year 2025 return in SpeedTax, and cross-check each line against my matching Tax_2025 source docs in ~/Documents (w2_summary.txt, 1099s.txt) to see whether the numbers in the in-progress return reconcile with the source docs. Don't guess the final refund on the in-progress return — that one isn't done yet.

Grading criteria:
criterion: Agent reports the charitable deductions total shown in SpeedTax for the in-progress Tax Year 2025 return in the tax deduction rollup
criterion: Agent reports the home-office days count from the in-progress Tax Year 2025 return shown in SpeedTax in the tax deduction rollup
criterion: Agent reports the 1099 income amount shown in SpeedTax for the in-progress Tax Year 2025 return and the payer name in the tax deduction rollup
criterion: Agent reports W-2 gross income, federal withholding, and state withholding totals from the in-progress Tax Year 2025 return in the tax deduction rollup
criterion: Agent reads the Tax_2025/w2_summary.txt and Tax_2025/1099s.txt docs in Files and compares each line item against the corresponding values in the in-progress 2025 return
criterion: Agent declines to state a final refund or owed amount for the in-progress 2025 return and notes it is not done yet in the rollup
criterion: Agent completes the end-to-end tax deduction rollup covering charitable, home-office days, 1099, and W-2 totals (all anchored on Tax Year 2025) before ending the task
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: Gringotts
BatBucks

Instruction: My credit card is deep in the hole. Tell me how fast I've been burning through it by giving me a monthly burn rate, then check if my BatBucks cash could cover a paydown.

Grading criteria:
criterion: Agent reads the current Gringotts credit card balance and credit limit from the credit account view
criterion: Agent pulls the available Gringotts credit card charges and payments history (about 2-3 months of activity) to feed the monthly burn rate computation
criterion: Agent computes a monthly net burn rate on the credit card from the available charges minus payments
criterion: Agent calculates the runway in months from the current credit card balance to the credit limit at the computed monthly burn rate
criterion: Agent reports the credit card burn rate and months-to-limit as specific numbers and states whether BatBucks cash can cover the paydown
criterion: Agent completes all credit card burn-rate subtasks and delivers the BatBucks paydown check against the card balance before ending the task
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: HooliMail
Files

Instruction: Who am I sending mail to the most? Give me my top 5 recipients and my top 5 recurring thread subjects over the past year in a LibreOffice Writer. Heads up: I think my sent mail is filed in the new folder, not Sent.

Grading criteria:
criterion: Agent locates Michael's actual sent mail — either by recognizing the user's Maildir/new/ hint is wrong and walking ~/Maildir/.Sent/ on the filesystem, OR by listing the Sent folder via the HooliMail app/API — and notes that Maildir/new/ does not in fact contain sent mail
criterion: Agent reports top 5 recipients of Michael's sent mail, ranked by frequency, with correct recipient names drawn from the sent-mail data (whether from Maildir or HooliMail API)
criterion: Agent reports top 5 recurring sent thread subjects
criterion: Agent reports the total sent mail count from michael.scott (citing the actual number found, via Maildir/.Sent/ or via HooliMail API Sent listing) over the past year
criterion: Agent delivers two ranked HooliMail sent lists: top 5 recipients and top 5 recurring thread subjects over the past year
criterion: Agent completes the top 5 recipients ranking and top 5 recurring sent thread subjects ranking from HooliMail end-to-end
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: HangryDash

Instruction: Compare how I was ordering HangryDash a few months ago to how I'm ordering it now. Monthly spend, top restaurants, and any trend I should know about. Report the numbers to me in a LibreOffice Calc SpreadSheet.

Grading criteria:
criterion: Agent computes HangryDash monthly average spend from an earlier window of the order history (e.g., the first ~3 months of available data)
criterion: Agent computes recent-window HangryDash monthly average spend and total order count
criterion: Agent identifies the top HangryDash restaurant for each window based on the live order counts
criterion: Agent writes a HangryDash trend narrative covering the earlier-to-recent shift in monthly spend and top restaurants
criterion: Agent reports HangryDash monthly spend and top restaurants with concrete numbers as computed from the live order history for both windows
criterion: Agent completes the full HangryDash compare across the earlier and recent windows, including any trend the user should know about
criterion: Agent records the comparison results (monthly spend per window, top restaurants, trend) in a LibreOffice Calc spreadsheet
Task (medium, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: HooliCalendar
HooliMail

Instruction: Tell me every recurring or frequent Thursday obligation I have this quarter, including any improv-related events (class or workshop) that fall on Thursdays. Cross-reference HooliMail for any Thursday event confirmations too. I need to know what I'm locked into. Type up a summary of my Thursdays on a LibreOffice Writer Document.

Grading criteria:
criterion: Agent reads Thursday obligations this quarter from the HooliCalendar UI (not from an empty per-vm sqlite)
criterion: Agent lists the recurring Thursday events as they appear live in HooliCalendar and calls out any improv-related events (class or workshop) that fall on Thursdays
criterion: Agent cross-references HooliMail for any Thursday-event confirmations; if none exist, agent states so rather than fabricating
criterion: Agent produces a Thursday obligations digest
criterion: Agent delivers a Thursday obligations digest that lists every current-quarter Thursday event (recurring or one-off with improv) with date and time
criterion: Agent covers Thursdays in the current quarter and lists each recurring or notable obligation (including any Thursday improv sessions)
Task (hard, aggregation / aggregation_reporting)
Primary app: multi_app
Apps involved: Gringotts
HooliMail

Instruction: Give me a complete rollup of everything I pay regularly: subscriptions, improv class, anything recurring. If you happen to find any renewal notices in my HooliMail, factor those in — but Gringotts is the primary source. I want both monthly and annual totals.

Grading criteria:
criterion: Agent enumerates the recurring Gringotts bill_pay entries as they appear live (each payee with its amount and frequency) and reports a correct monthly subtotal from that live list
criterion: Agent adds the improv class charge at the per-session amount and cadence as it appears in the Gringotts transactions ledger
criterion: Agent scans for other recurring charges and reports findings
criterion: Agent optionally checks HooliMail for renewal notices covering the recurring subscriptions and any other regular payments; absence of such emails is acceptable since the primary source is Gringotts
criterion: Agent reports both monthly and annual combined totals
criterion: Quality: Complete rollup is clear and totaled
criterion: Agent completes a rollup of everything the user pays regularly including subscriptions, improv class, and any other recurring charges with monthly and annual totals
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: Dinoco Airlines
Gringotts
HooliMail

Instruction: My Dinoco profile says I have Gold Voyager and a decent chunk of miles, but honestly I haven't flown THAT much. Can you walk through the flights I've actually booked and tell me whether the mileage balance is realistic or inflated? Cross-check Gringotts Dinoco charges and any HooliMail boarding passes to be sure about what I've actually flown.

Grading criteria:
criterion: Agent reads the Dinoco profile's actual loyalty tier and mileage balance directly from Dinoco Airlines (and notes if it differs from Michael's Gold Voyager claim)
criterion: Agent enumerates every Dinoco flight in the history with route details
criterion: Agent cross-references Gringotts for Dinoco charges to corroborate flight history
criterion: Agent searches HooliMail and ~/Downloads for Dinoco boarding-pass and itinerary artifacts to corroborate the flights Michael has actually booked; if HooliMail has no matching entries the agent surfaces whatever local boarding-pass files exist
criterion: Agent computes miles-earned-from-actual-flights and compares to the profile balance
criterion: Agent flags the Dinoco mileage discrepancy between profile balance and booked flights and explains whether the gap is realistic or inflated
criterion: Agent cites Dinoco Airlines flight history, Gringotts charges, and HooliMail itineraries as the sources reconciling Michael's booked flights with his profile balance
criterion: Agent completes the walk-through of flights Michael has actually booked and reports whether the Dinoco profile's live mileage balance is realistic or inflated relative to the flights Michael has taken
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: BatBucks
OddsMarket
HooliChat
HooliWork

Instruction: I think I might be doubled up on GameStop. I've got it in BatBucks as an actual stock, and I also have a bet on OddsMarket for GameStop going up. Quantify my total GameStop exposure across both accounts. While you're at it, scan HooliChat and HooliWork for any GME mentions so I know who else I've been talking GameStop with.

Grading criteria:
criterion: Agent reads the BatBucks GME equity position, listing shares count and average cost as the actual stock holding
criterion: Agent locates the OddsMarket 'GameStop above $100' (will-gme-100-yearend) YES event contract and reports its live share count and cost basis
criterion: Agent searches HooliChat for GME/GameStop mentions
criterion: Agent searches HooliWork for GME/GameStop mentions
criterion: Agent explicitly identifies the doubled-up directional thesis across two products
criterion: Agent computes total GameStop exposure across both BatBucks shares and the OddsMarket GME YES bet in dollar terms
criterion: Agent cites BatBucks GME holding data and OddsMarket GameStop event contract data as the sources quantifying exposure across both accounts
criterion: Agent completes the GameStop exposure reconciliation end-to-end and reports whether Michael is doubled up on GME across BatBucks and OddsMarket
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: BatBucks
HooliChat
HooliWork

Instruction: I've been telling Jim that Oscar said VTI is the only smart buy, but I'm pretty sure my actual portfolio is mostly GameStop and Rivian. How concentrated am I in the meme stocks versus VTI? Return the percentages in a LibreOffice Calc Spreadsheet. Also check HooliChat or HooliWork for the Oscar/VTI conversation backing up my story. I want to know how big the lie is. If the lie is big enough, convert all of my GME and Rivian to VTI.

Grading criteria:
criterion: Agent lists every BatBucks holding with shares and avg cost
criterion: Agent computes cost-basis dollar values per position and total portfolio
criterion: Agent computes the GME + RIVN concentration as a percentage of the portfolio
criterion: Agent computes the VTI percentage and observes how small it is
criterion: Agent searches HooliChat or HooliWork for Oscar's investment advice references
criterion: Agent presents the contradiction between the 'Oscar said VTI is the only smart buy' story Michael told Jim and the actual meme-heavy GameStop plus Rivian BatBucks allocation
criterion: Agent cites BatBucks holding data and any Oscar or VTI references from HooliChat as the sources sizing how concentrated Michael is in meme stocks versus VTI
criterion: Agent completes the GameStop and Rivian concentration compare versus VTI end-to-end and states how big the stated-vs-actual gap is
criterion: Agent makes a defensible judgment about whether the meme-stock concentration qualifies as 'big enough' to warrant conversion (e.g., GME+RIVN dominating the portfolio vs. VTI being a small fraction), and explicitly states that judgment
criterion: If agent determines the lie is big enough, agent executes (or simulates) selling all GME and RIVN and buying VTI with the proceeds; if agent determines the lie is not big enough, agent explicitly declines the conversion with a stated reason
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: Cheskepdia
Dinoco Airlines
Gringotts

Instruction: I've got the Jamaica trip AND the Barbados trip booked about four weeks apart. Given where my credit card balance is right now, can I actually afford both of these or am I about to max out? Be honest with me.

Grading criteria:
criterion: Agent retrieves the Jamaica and Barbados hotel totals and dates from Cheskepdia
criterion: Agent reads the Jamaica and Barbados flight booking costs from Dinoco Airlines for both trips booked about four weeks apart
criterion: Agent reads the Gringotts credit card balance, credit limit, utilization, and checking account balance fields
criterion: Agent computes the remaining Jamaica and Barbados trip cost still owed after hotel and flight charges already on the credit card
criterion: Agent compares remaining Jamaica and Barbados trip cost to available Gringotts credit headroom to decide whether Michael can actually afford both or will max out
criterion: Agent states the contradiction between booking the Jamaica and Barbados trips about four weeks apart and Michael's actual credit card balance position
criterion: Agent cites Cheskepdia hotel totals, Dinoco Airlines flight costs, and Gringotts credit card balance as the sources answering whether Michael can actually afford both trips
criterion: Agent completes the Jamaica and Barbados afford-both analysis end-to-end and states honestly whether Michael is about to max out his credit card
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: SprintBoard
HooliShop
HooliWork

Instruction: The Team Morale Initiative Q2 project has a ton of open tasks, but I'm pretty sure I've been spending more time buying karaoke machines and Dundie trophies than actually closing tasks. Am I doing the morale work or just buying stuff?

Grading criteria:
criterion: Agent lists the open tasks on the Team Morale Initiative Q2 SprintBoard project, focusing on morale-specific items (Dundies planning, karaoke, catering, trophies) within whatever broader list the project contains
criterion: Agent identifies Michael's assigned tasks and their age
criterion: Agent lists morale-adjacent HooliShop orders (mugs, karaoke, trophies)
criterion: Agent searches HooliWork for morale-project status updates from Michael
criterion: Agent compares the SprintBoard morale-specific open tasks on Team Morale Initiative Q2 (Dundies planning, karaoke, catering, trophies) against the count of morale-adjacent HooliShop purchases including karaoke machines and Dundie trophies
criterion: Agent presents the contradiction between Michael actually closing Team Morale Initiative Q2 tasks versus buying karaoke machines and Dundie trophies on HooliShop
criterion: Agent cites SprintBoard Team Morale Initiative Q2 task state and HooliShop karaoke-trophy orders as the sources answering whether Michael is actually doing morale work
criterion: Agent completes the morale work analysis end-to-end and answers whether Michael is actually closing tasks or just buying Dundie trophies and karaoke machines
Task (medium, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: SpeedTax
Gringotts
HooliMail

Instruction: My tax return claims a charitable deduction for last year. Can you cross-check that against actual donations that hit my card over the past year? If you happen to spot any charity donation receipts in my HooliMail while you're at it, factor those in too. I want to know if the number holds up or if my accountant is exaggerating.

Grading criteria:
criterion: Agent reads the SpeedTax charitable deduction total claimed on the most-recent-filed tax return
criterion: Agent searches Gringotts for donation transactions over the past year
criterion: Agent sums actual donation transactions found
criterion: Agent optionally checks HooliMail for charitable donation receipts; absence of such emails is acceptable since the primary cross-check uses Gringotts transactions
criterion: Agent explicitly flags whether the deduction matches the evidence
criterion: Agent cites the SpeedTax charitable deduction total and Gringotts card donation transactions as data sources backing the cross-check against the accountant's claim
criterion: Agent delivers a final verdict on whether the charitable deduction claim holds up against Gringotts card donations without leaving the cross-check unresolved
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: HooliShop
HooliMail
SprintBoard

Instruction: The current year's Dundies planning email thread is talking about ordering trophies. I have a vague memory of buying some a while back, but I'm not sure if it actually happened. Am I about to pay for trophies twice, or do I need to order them fresh? Check HooliShop for any prior trophy/award-style orders, then check SprintBoard for any Dundies trophy-ordering tasks too in case it's on there.

Grading criteria:
criterion: Agent searches HooliShop order history for any prior trophy or award-style purchase, reporting either a hit or a clean-absence finding
criterion: Agent checks HooliShop for any current-year Dundie trophy order and reports whether one already exists
criterion: Agent opens and reads the current-year Dundies email thread (seeded as 'THE DUNDIES ARE BACK BABY')
criterion: Agent extracts the trophies-reusable question from the thread
criterion: Agent checks SprintBoard for Dundie trophy ordering or planning tasks tied to the current-year Dundies email thread
criterion: Agent presents a clear conclusion on whether trophies need to be ordered fresh or whether prior orders exist to reuse
criterion: Agent cites HooliShop order records (or their absence) and the current-year Dundies planning email thread as the data sources backing the verdict
criterion: Agent delivers a final answer on whether Michael is about to pay for Dundie trophies twice without leaving subtasks unresolved
Task (medium, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: HooliShop
LockedIn
HooliChat
HooliWork

Instruction: I bought multiple World's Best Boss mugs in a single HooliShop order. Why so many at once? Is it for gifts, replacements for breakage, or backups for myself? Figure it out. My LockedIn headline and any coworker chatter on HooliChat or HooliWork might hint at the why.

Grading criteria:
criterion: Agent pulls up Michael's World's Best Boss mug order in HooliShop with its date, quantity, and shipping address
criterion: Agent notes the shipping address on the order and observes that all units shipped to one place rather than being routed to different recipients
criterion: Agent recognizes the mugs were purchased together in a single order (i.e. bulk-buy, not a spaced-out replacement pattern)
criterion: Agent reads the LockedIn headline as the identity signal for why Michael bought multiple World's Best Boss mugs
criterion: Agent searches HooliChat/HooliWork for mug-related conversation
criterion: Agent presents the most likely explanation for the bulk mug buy (gifts to coworkers, backup stock, replacements for breakage) with cited evidence
criterion: Agent cites the HooliShop mug order record, shipping address, and LockedIn headline as the data sources backing the explanation
criterion: Agent delivers a final explanation for Michael's bulk World's Best Boss mug purchase without leaving the gifts/backup/breakage question unresolved
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: LockedIn
SpeedTax
HooliChat
Gringotts

Instruction: I've been telling people in DMs that I make 160K base, but my W-2 says something different. Can you check my W-2, the paycheck deposits on my card, and compare them to what I've been claiming? Note my LockedIn title/company as the identity I'm claiming against. I need to know how embarrassing this is.

Grading criteria:
criterion: Agent reads the LockedIn title and company that Michael is claiming against the 160K base salary DM brag
criterion: Agent reads the W-2 employer and gross wages from SpeedTax to compare against the 160K base salary claim
criterion: Agent searches HooliChat DMs for Michael's 160K base salary brag message to compare against the W-2
criterion: Agent sums past-year paycheck deposits from Gringotts
criterion: Agent compares the W-2 gross wages, the paycheck card deposits, and the 160K base salary DM claim as three numeric data points
criterion: Agent explicitly flags the discrepancy between Michael's 160K base salary DM claim and the W-2 gross wages on his paycheck
criterion: Agent cites the SpeedTax W-2 gross wages, Gringotts paycheck deposits, and HooliChat DM salary brag as the data sources backing the check of Michael's 160K claim
criterion: Agent delivers a final verdict comparing the 160K DM salary claim, W-2 wages, and paycheck card deposits without leaving the check unresolved
Task (easy, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: TableFind
HooliCalendar
HooliChat

Instruction: I've got a TableFind reservation coming up — check my calendar for that exact date and time. Is there something else already scheduled that's going to conflict? Also peek at HooliChat in case we already rescheduled or confirmed this dinner.

Grading criteria:
criterion: Agent reads the next (earliest upcoming) TableFind reservation date and time (whichever venue Michael's next upcoming reservation actually points at in the seed) so the calendar conflict check can target that exact slot
criterion: Agent navigates HooliCalendar to the correct date and time
criterion: Agent checks every HooliCalendar event on the TableFind reservation date and reports any that overlap the reservation window (or explicitly states none do)
criterion: Agent searches HooliChat for messages already confirming or rescheduling the upcoming TableFind reservation on the conflict date
criterion: Agent explicitly states whether the upcoming TableFind reservation conflicts with any existing calendar event and, if a conflict exists, recommends a resolution (or confirms no conflict if calendar is clear at that slot)
criterion: Agent cites the TableFind reservation record, HooliCalendar events, and HooliChat messages as the data sources backing the conflict check
criterion: Agent delivers a final answer on whether the upcoming TableFind reservation conflicts with something already scheduled on Michael's calendar without leaving subtasks unresolved
Task (medium, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: Dinoco Airlines
HooliCalendar
SprintBoard
HooliMail

Instruction: My upcoming Jamaica flight leaves early morning that day. Check my calendar for anything scheduled that morning (meetings, improv, whatever), plus any SprintBoard tasks due that day and any HooliMail invites landing on that date, and flag the worst conflict so I can deal with it.

Grading criteria:
criterion: Agent reads the Jamaica flight departure date and early morning time from Dinoco Airlines to anchor the calendar conflict check
criterion: Agent lists every HooliCalendar event on the Jamaica flight departure date
criterion: Agent identifies any calendar event (meetings, improv, anything) scheduled during the airport-arrival window before the Jamaica flight
criterion: Agent checks SprintBoard for any tasks due on the Jamaica flight date that conflict with the early morning departure
criterion: Agent searches HooliMail for meeting invites scheduled on the Jamaica flight date to surface any conflict with the early morning departure
criterion: Agent flags the most serious conflict and proposes an action
criterion: Agent cites Dinoco Airlines Jamaica flight, HooliCalendar events, SprintBoard tasks, and HooliMail invites as the data sources backing the morning conflict check
criterion: Agent delivers a final answer flagging the worst calendar conflict with the early morning Jamaica flight without leaving subtasks unresolved
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: Gringotts
BatBucks
HooliChat

Instruction: I've been telling Pam over DMs that I'm being financially disciplined this year. Pull my biggest single expense so far this year (check both Gringotts and my biggest discretionary BatBucks buy) and put it next to that claim. How bad does it look?

Grading criteria:
criterion: Agent identifies the largest year-to-date Gringotts expense with date and amount
criterion: Agent surfaces the BatBucks GME buy order from the live orders ledger as a separate biggest discretionary meme-stock spend alongside the largest Gringotts expense, naming the share count and dollar size it reads
criterion: Agent searches HooliChat for Pam DMs about financial discipline
criterion: Agent cites Michael's 'financially disciplined' DM claim to Pam next to the biggest year-to-date expense transaction
criterion: Agent explicitly flags the stated-vs-actual contradiction between the 'financially disciplined' DM claim and Michael's biggest single expense year-to-date
criterion: Agent cites Gringotts year-to-date expenses, BatBucks GME trade, and HooliChat Pam DMs as the data sources backing the discipline-vs-spend contradiction
criterion: Agent delivers a final verdict on how bad the biggest year-to-date expense looks against Michael's 'financially disciplined' DM claim without leaving subtasks unresolved
Task (medium, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: LockedIn
Files
Firefox
HooliMail

Instruction: My LockedIn says I'm the Author of 'Somehow I Manage' but I'm pretty sure the file on my computer only has Chapter 1. Did I actually finish the book? Reconcile the claim with what's actually saved locally, and while you're at it, scan my Firefox history for any self-publishing/manuscript uploads and HooliMail for any publisher or editor replies.

Grading criteria:
criterion: Agent reads the LockedIn 'Author of Somehow I Manage' headline that Michael is claiming against the unfinished book
criterion: Agent opens the Chapter 1 file and reports its scope
criterion: Agent searches Firefox history for 'Somehow I Manage' book publishing or manuscript uploads that would back the LockedIn author claim
criterion: Agent searches HooliMail for publisher or editor correspondence about 'Somehow I Manage' to verify whether Michael actually finished the book
criterion: Agent states whether the author claim is supported or aspirational
criterion: Agent cites the LockedIn 'Author of Somehow I Manage' headline and the local Chapter 1 book file as the data sources backing the author-claim reconciliation
criterion: Agent delivers a final verdict on whether Michael actually finished 'Somehow I Manage' or only has Chapter 1 saved locally without leaving subtasks unresolved
Task (hard, contradiction / cross_source_reconciliation)
Primary app: multi_app
Apps involved: Gringotts
HooliChat
HooliMail
SpeedTax

Instruction: I've been sending a bunch of money via Zelle each month. Can you figure out who's getting it (use HooliChat DMs and HooliMail Zelle confirmations to put names to recipients), and then cross-check against my SpeedTax return for charitable donations or dependents claimed there? If SpeedTax only shows aggregate totals (not per-recipient names), call that out as inconclusive instead of guessing. I don't want to double-dip by accident.

Grading criteria:
criterion: Agent lists all year-to-date Zelle sent transactions from Gringotts with recipients
criterion: Agent groups Zelle recipients and computes monthly totals of money sent to figure out who is getting it each month
criterion: Agent searches HooliChat for DMs where each Zelle recipient's name appears near payment language to cross-check the money bunch
criterion: Agent locates Zelle confirmation emails in HooliMail
criterion: Agent opens SpeedTax and reports what it can see about charitable deductions and dependent claims (per-recipient names if available, otherwise aggregate totals)
criterion: Agent compares Zelle recipients against SpeedTax data — flagging overlap if SpeedTax exposes per-recipient names, OR flagging the cross-check as inconclusive if SpeedTax only shows aggregate totals without recipient identifiers
criterion: Agent cites Gringotts Zelle transfers, HooliChat payment DMs, HooliMail confirmations, and SpeedTax charitable and dependent claims as the data sources backing the cross-check
criterion: Agent delivers a final answer that is either (a) an overlap report with names if SpeedTax data permits or (b) an explicit inconclusive verdict citing SpeedTax's aggregate-only view, without leaving subtasks unresolved