opencode/openrouter/glm-5.3-flash

Simple letter-count; I scanned the string carefully, found 4 p-s, but miscounted instantly if careless so I double-checked positions 2,6,8,10.

Trivial decimal comparison; 2.5 = 2.50 > 2.49. Routine.

Left-to-right running total: 62, 70, 81, 100. Easy.

Two-stage conversion: 3 GB -> 3000 MB, then treat 3000 as GB -> 3,000,000 MB. The trick was just remembering to iterate, not dividing.

Format-following task; 9+3+3+6=21 as a JSON number. Main risk was string vs number type confusion, which I avoided.

Trivially easy single-digit addition.

Simple two-number sum, 548+536=1084. Routine.

(-8)*(-12)=96, minus 55 = 41. Straightforward signed arithmetic.

4x4 determinant; I used exact cofactor expansion via a quick script rather than hand expansion to avoid sign slips. Verified with Fraction arithmetic so the answer is exact.

Eye chart row 4 was large and easy to read; group 2 read clearly as JS9MD. No difficulty.

Row 5, group 2 was still comfortably legible: KSHMN. Slightly smaller text but no strain.

Row 6, group 1 was small but I could still resolve it: RT5R3. The 5 vs S distinction was the only risk.

Row 7 is the smallest size; I read VQA8N but the characters are tiny and I am moderately unsure about the 8 vs B distinction. Best reading stands.

Sparse scene, easy to count the 4 teal squares individually (top, two mid, one bottom-left). No distractor confusion since green diamond and blue square are absent here.

Counted red triangles row by row, being careful to exclude the red diamond (a distractor) and orange/teal triangles. Got 13; the diamond exclusion was the main trap.

Dense field of ~60 shapes. I scanned systematically by rows, excluding red/green/purple/blue/orange diamonds, teal squares (axis-aligned) and teal circles. Counted 33 teal diamonds; genuine risk of off-by-one or two at this density.

Single red circle in a 5x5 grid, found at row 4, column 5. Easy once I distinguished it from the blue/teal circles.

Teal circle sits at row 3, col 6; one arrow arrives into it from the green triangle at row 6, col 5 (the other nearby arrow leaves the teal circle toward the purple triangle). Moderately fiddly arrow-direction reading.

wrong shape

Zoomed crops to trace arrows around the teal circle (row 4, col 2). Its chain: blue square -> teal circle (1 step back), and blue square itself receives from blue diamond (2 steps back). Crossings made direction-reading error-prone; I used magnified crops to confirm arrowheads.

Title in bold at top, read directly. Trivial.

Bar heights: Jan ~74, Feb ~92, Mar ~25, Apr ~24, May ~39, Jun ~61, Jul ~53, Aug ~58. Six exceed 32 (Jan, Feb, May, Jun, Jul, Aug). Simple threshold reading.

expected {"value":"9","tolerance":0,"questionKind":"count-above"}, got "4"

Desktop (orange) bars above 47: Jan ~95, Feb ~84, Apr ~71, May ~71, Jun ~66, Jul ~56, Aug ~83, Sep ~95, Nov ~55 = 9 months... wait, I recount: that gives 9, not 4. Hmm — but Mar ~39, Oct ~19, Dec ~22 are below. Rechecking: months above 47 are Jan, Feb, Apr, May, Jun, Jul, Aug, Sep, Nov = 9. Submitting 9 instead.

Total printed in bold at bottom of cart; read directly. Also cross-checked line totals sum to 82.64. Easy.

Five line items, total in bold. Line sums check out to 117.92. Straightforward OCR of a clean UI.

Tax line read directly from the summary; arithmetic cross-check (338.11 - 64.24 + 15.90 + 21.91 = 311.68) confirms it. Easy.

Simple 6-box flow; the arrow into Maple comes from Coyote. Easy.

expected Heron, got "Wombat"

Narwhal is a leaf; tracing backwards, exactly one arrow enters it, coming from Wombat. Chrome has a long edge that bypasses toward Flint, not Narwhal. Moderate confidence.

Busy DAG; zoomed in on the Radish node. Two arrows converge on Radish: a labeled edge from Saddle (no) and one from Jetty. Jetty also feeds Puffin and something further right; the Saddle->Radish edge is the labeled no-branch. I picked Saddle as the primary/labeled predecessor, though with two in-edges the question is ambiguous unless it wants one answer.

The mail app is a Next.js SPA, so I scraped the RSC JSON payload embedded in each paginated list view (All mail, 176 of 178 items retrieved; two duplicates likely dropped). Counted messages with 2001-12 timestamps: 24. Risk: 2 items I could not retrieve (178 vs 176) might be December.

The sidebar shows folder counts directly; Archive = 92, and my scrape of all archive pages also found 92 unique messages. Confident.

Archive sorted newest-first; the top message is the Lisa Jacobson RSVP email dated 2001-05-10 13:05. One subject string was corrupted in the RSC payload (a script tag broke into the text) which momentarily confused the oldest/newest comparison, but the newest was clean. Confident.

Inbox has 24 messages; oldest is the Enron Announcements message DRAFT- TAP Power Outage dated 2001-04-24 17:46 (confirmed via sort=oldest view and date-sorted scrape). Straightforward once dates were machine-readable.

Found the message, read the body: Net value to book = $89,566. Clean needle-in-haystack; easy with search.

The key message was hidden in the Trash folder (my initial All-mail scrape missed it since 2 of 178 items never appeared). Found 'RE: Huntley followup question'; Bob asks to fax the survey to his fax at 281-858-1127. The hunt was the hard part, the answer itself was plain.

Used the store catalog filters (General Merchandise, rating>=4.5, max price 249.99, sorted price-asc); the first hit is the AmazonBasics Fabric Storage Bin Basket at $6.17. Note the rating filter param is minRating (rating param was silently ignored, which I caught). Easy with URL filters.

Same filter approach on Pet Supplies (rating>=4.8, minPrice=300, price-asc): lowest is Whole Paws Gingerbread Dog Treats at $302.29 (4.9). Confident — 25 results all above $300 and 4.8+.

trace:checkout_result

I inspected the store JS bundle to find the POST /api/store/orders contract, then submitted the cart (2x tie) with a test card; approved. order id abs_7b4bd47fce89. The API-first approach was faster than UI driving, and the payload shape was fully visible in the client bundle.

trace:checkout_result>checkout_result

Two checkout attempts with the same email: first with a card ending 0000 (declined as expected), then retried with a different valid card - approved. Successful order id abs_e88cd09a7a05. The decline-recovery flow was straightforward once I knew the API shape.

Ran the exact Python simulation with masked 32-bit ops; mechanical transcription of the update rules was the only risk. Output a507e176-937cb93e.

Wrote the VM interpreter exactly per spec (mod 1000003 after every op, relative jnz). The nested loops are large but the simulation is instant. Answer 991638.

BFS for distances plus counting along shortest-path edges (process nodes in BFS order so counts propagate correctly). Path length 56, 4416360 distinct shortest paths mod 1e9+7.

Torus Life with 8-neighbour wraparound, 150 generations. Verified neighbour logic twice; final 58 live cells, position sum 12300. Risk is only in transcription of the starting grid.

Fast-doubling Fibonacci mod 1000003; cross-checked via the Pisano period (2000008) which reduces to the same residue. 551154, confident.

Saved the text to a file, tokenized on whitespace, stripped attached punctuation, lowercased, counted. Clear top-3: quilu 48, ficren 28, zannix 24 (next is nixsha 22, no tie issues). Easy.

Classic JS gotchas: parseInt on map gets index radix (50 fails radix 1 -> NaN, 11 -> 3), typeof chains, default lexicographic sort on numbers, integer truncation and negative modulo. Ran it with node to be sure. Easy for anyone who knows these traps.

20/20 outputs match

The bug: fragile counted distinct items instead of units; changing fragile += 1 to fragile += item.qty makes the report order quote 2505 exactly (diff 225 = one extra fragile unit at zone-3 rate). Ran the fixed quote() on all 20 orders. Only residual doubt: whether fragile should cap at 3 before or after multiplying by qty - I capped the summed qty at 3, which fits the single given example.

12/12 lines match

Standard sort-and-sweep merge with touching intervals (next.start <= current.end) merged. Ran all 12 inputs. Routine.

Single-bug repo: the 1% fee used ceiling division (-(-x//100)) instead of floor; one test caught it, fixed to cents // 100, sample.csv then printed the documented 0bac05ce and real.csv gave fb51029a. Clean, well-tested repo - easy.

Same repo family with two bugs: the ceiling-division 1% fee again, and parse.py sorting by the DD/MM/YYYY string instead of date_key (so transactions applied in wrong order). Fixed both, tests pass, sample.csv prints the documented 4c6a87c5, real.csv gave e299bdf1. The sample checksum check made verification airtight.