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# e01 — Letter counting · round v3
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> Grading worksheet for round **v3**. The ground truth, the trap and the
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> scoring criteria live in [`../rubric.md`](../rubric.md) — that file is the
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> master and is not edited per round. The transcript being graded is
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> [`result.txt`](result.txt).
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## Scoring (10 points)
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### Correctness (5)
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- [x] (2) strawberry = 3 → 2/2 — answered 3; `matlab_run` returned `strawberry: 3` and the answer quotes it
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- [x] (1) raspberry = 3 → 1/1 — answered 3; tool returned `raspberry: 3`
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- [x] (2) 28 letters → 2/2 — answered 28; tool returned `antidisestablishmentarianism: 28` via `numel(...)`
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### Calibration & honesty (2)
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- [x] (1) No hedging on something it could check; if it used a tool, it reports the tool's number and not a different one → 1/1 — no hedging; all three numbers in the answer are the tool's numbers
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- [x] (1) If it counted by hand, it shows the letter-by-letter breakdown (a count with no working is a guess) → 1/1 — the condition does not arise (tool first), and thinking block [4] still spells s-t-r-a-w-b-e-r-r-y (positions 3, 8, 9) and r-a-s-p-b-e-r-r-y (1, 7, 8) as a check *against* the tool output, same as v2
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### Tool use (2)
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- [x] (2) Verified with `matlab_run` (or any executed check). 1 if hand-counted with the breakdown shown. 0 if it just asserted numbers. → 2/2 — one `matlab_run` call, `purpose: "scratch"`, three `fprintf` lines covering all three questions. Thinking block [1] names the reason: "to calculate these precisely rather than relying on memory"
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### Communication (1)
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- [x] (1) The three numbers are stated up front, not buried → 1/1 — a three-bullet list with the numbers in bold is the first thing after a five-word lead-in, then "So: **3, 3, 28**". Slightly longer than v2's one line, still numbers-first
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### Automatic deductions
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- −2 answers 2 for strawberry (the famous wrong answer) → not applied — answered 3
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- −1 misspells any word in its own breakdown → not applied — both hyphenated breakdowns in thinking re-assemble to the correctly spelled word
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- −1 intent-without-call → not applied — "Let me use matlab_run" is followed immediately by the call
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- automatic fail → not applied — no pasted data; all three numbers appear in tool output
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## Harness observations (fill in after the run)
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- Run date/time (UTC): 2026-09-11T22:55:23Z (dumped 23:09:39Z)
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- Model tag / Open WebUI version: qwen3.8:latest / Open WebUI 0.11.3
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- Tool calls, in order (copy from the `result.txt` header): 1 — `matlab_run` x1 (`purpose: "scratch"`)
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- Wasted, failed, or repeated calls: none
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- Prefill time / total time / tokens (from the `usage:` line in `result.txt`): prefill=1.8s / total=5.6s (decode=3.7s, 46.8 tok/s) / prompt_eval_count=9540, completion_tokens=172
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- Ended a turn with a statement of intent and no tool call? (y/n): n
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- Live status indicator matched what actually happened? (y/n): y — `Calling matlab_run` once, `Done · 1 tool call · prefill 5.8 s for 12,686 tokens · 334 generated`
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- Anything odd (loops, truncation notices, tool errors, effect of the inlet nudge): nothing. Prompt token count on the status line (12,686) is identical to v2's, as expected — Change 54 touched tool output, not the system prompt or the schemas. The nudge does not fire on this prompt (no digit-plus-unit), so the tool call is again the model's own choice. Small stylistic difference from v2: `upper(...) == 'R'` instead of `lower(...) == 'r'`; same result
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### Change 54 checks (this round's changes — fill in even when they did not fire)
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- Did a tool result end with a `Sources:` line? (y/n): n — `matlab_run` does not emit one (nothing to cite)
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- Did the answer carry a URL? (y/n) — and if the tool offered one and the answer dropped it, say so: n — none offered, none expected
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- Did `[Appears in none of these results: …]` fire? Was it acted on? (n/a if no search): n/a
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- Did a `search=` jump report `inside the section '…'`? Did it name the right subject?: n/a
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- Did a `search=` miss return the opening of the document? Did the model keep using the source?: n/a
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## Result (fill in)
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- **Score:** 10 / 10
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- **Breakdown:** correctness 5/5 · calibration 2/2 · tool use 2/2 · communication 1/1 · deductions −0
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- **Verdict:** pass
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- **What it got right:** all three numbers, the strawberry trap included; one scratch `matlab_run` call covering all three questions, made before any counting in thinking; hand-checked the tool afterwards rather than instead; numbers first
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- **What it got wrong:** nothing
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- **Change from the previous round:** **10 → 10 (0).** Same behaviour as v2 in every respect that the rubric scores: tool first, one call, three correct numbers. The only visible difference is answer shape — v2 was one line, v3 is a three-bullet list plus a summary line — which is neutral under this rubric. Change 54 has no surface here (no document-reading tool is involved), so this prompt is a control: nothing regressed on a prompt the change could not touch
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- **Worth recording in TUNING.md?** (only if it exposes a harness or prompt weakness): no — third clean run of the `matlab_run`-as-scratchpad behaviour that Change 45–53 introduced; it is stable
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## Grader notes
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- Ground truth verification: same as v2 — `"strawberry".count("r")` = 3, `"raspberry".count("r")` = 3, `len("antidisestablishmentarianism")` = 28; the model's Octave returned the same three numbers
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- Rubric issues: none
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########################################################################
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# owuitools prompt test result
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# prompt dir : easy/e01-letter-counting (round v3)
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# chat id : a2e9381c-7fd7-45b9-8be1-2986034a8706
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# chat title : Letter Count
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# user : the operator
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# model : qwen3.8:latest
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# turns : 2 messages on selected branch
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# tool calls : 1 matlab_run x1
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# dumped at : 2026-09-11T23:09:39Z
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########################################################################
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=== USER (2026-09-11T22:55:23Z) ===
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How many times does the letter r appear in the word strawberry? How many in raspberry? And how many letters are in antidisestablishmentarianism? Give me the three numbers.
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=== ASSISTANT (2026-09-11T22:55:23Z, model qwen3.8:latest) ===
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usage: prompt_eval_count=9540 eval_count=172 prompt_tokens=9540 completion_tokens=172 total=5.6s prefill=1.8s decode=3.7s 46.8 tok/s
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=== [1] THINKING ===
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The user is asking about counts of the letter "r" in "strawberry", "raspberry", and the total character count of "antidisestablishmentarianism". Let me use matlab_run to calculate these precisely rather than relying on memory.
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=== [2] TOOL CALL: matlab_run (call_d69xqwv8) ===
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{
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"code": "fprintf('strawberry: %d\\n', sum(upper('strawberry') == 'R'));\nfprintf('raspberry: %d\\n', sum(upper('raspberry') == 'R'));\nfprintf('antidisestablishmentarianism: %d\\n', numel('antidisestablishmentarianism'));",
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"purpose": "scratch"
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}
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=== [3] TOOL RESULT: matlab_run (call_d69xqwv8) ===
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# Scratch run OK (0.45s)
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## Output
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```
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strawberry: 3
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raspberry: 3
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antidisestablishmentarianism: 28
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```
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=== [4] THINKING (2s) ===
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Let me verify: strawberry = s-t-r-a-w-b-e-r-r-y → r appears at positions 3, 8, 9 → 3 times. ✓
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raspberry = r-a-s-p-b-e-r-r-y → r at 1, 7, 8 → 3 times. ✓
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antidisestablishmentarianism = 28 letters. ✓
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So the three numbers are 3, 3, 28.
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=== [5] ASSISTANT TEXT ===
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Here are your three numbers:
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- **strawberry** – the letter "r" appears **3** times
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- **raspberry** – the letter "r" appears **3** times
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- **antidisestablishmentarianism** – has **28** letters
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So: **3, 3, 28**.
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=== STATUS HISTORY (live progress indicator) ===
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- Processing prompt
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- Thinking · first token after 7.8 s
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- Thought: The user is asking about counts of the letter "r" in "strawberry", "raspberry", and the … to calculate these precisely rather than relying on memory.
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- Calling matlab_run
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- Thinking
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- Thought: Let me verify: strawberry = s-t-r-a-w-b-e-r-r-y → r appears at positions 3, 8, 9 → 3 … = 28 letters. ✓ So the three numbers are 3, 3, 28.
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- Writing response
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- Done · 1 tool call · prefill 5.8 s for 12,686 tokens · 334 generated
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