transcripts/README.md

Test transcripts — October 2026 bench

This archive holds every transcript, verdict and locked rubric behind the test results published on the site (prompt library, data report and methodology page). Everything in it is fictional test material: the sample inputs were written for the bench and contain no real clients, patients or cases.

Licence: everything in this archive (prompts, inputs, rubrics, transcripts, verdicts, results and the Claude Skills texts) is published under Creative Commons Attribution 4.0 International (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/). Credit: AI Professions (aiprofessions.ai). Also on GitHub: https://github.com/aiprofessions/prompt-benchmark

What is inside

Folder	Content
prompts/<prompt_id>/spec.yaml	The prompt, its fictional input, the 5-criterion rubric, round, and the rubric hash locked before the first run
prompts/<prompt_id>/<model>-runN.md	One transcript per run: header (model id, provider, start time UTC, duration, exit code, rubric hash), the exact query, the verbatim output
prompts/<prompt_id>/grades.json	Per-criterion verdicts (pass/fail + one-line reason) for every run, with the judge model
prompts-es2/<prompt_id>/	ES round 2 (10 new Spanish prompts, 2026-10-21): same layout as prompts/
tools/<prompt_id>/	Excel / Microsoft 365 task round: same layout as prompts/ (spec, transcripts, grades, calibration re-grades)
prompts/<prompt_id>/calib-<model>-runN.json	Judge-swap re-grades (only for the runs sampled for calibration)
bench/results.json	Aggregated results per prompt and model
bench/rubrics.lock.json	SHA-256 of (prompt, input, rubric) per prompt and the lock time
bench/calibration.json, bench/calibration-frpt.json	Judge-swap calibration, round 1 (EN/ES) and round 2 (FR/PT)
bench/spotcheck.json, bench/spotcheck-frpt.json	Spot-check of judge verdicts by the editor agent, round 1 and round 2
bench/*-fable*.json, bench/*-argon*.json	Calibration and spot-check for the added models (Claude Fable 5.1, Gemini 4 Argon)
bench/*-tools.json	Excel / Microsoft 365 round: results, rubric lock, calibration, spot-check
bench/*-es2.json	ES round 2: results, rubric lock, calibration, spot-check
skills/<skill>/<lang>/	Claude Skills round: current transcripts and per-run grades (grade-<model>-runN.json)
skills/<skill>/<lang>/v1.0/, v1.1/	ARCHIVED earlier skill versions (not the published text): the SKILL.md that was tested and its transcripts and grades
skills/<skill>/<lang>/stale/	Runs set aside because the skill text embedded in the query no longer matched the current SKILL.md; they were re-run and are kept for completeness
skills/_bench/	Skill specs and rubrics (specs.yaml; FR/PT: specs-frpt.yaml), rubric locks, results (all four languages), revision findings

Counts: 80 prompts, 1200 prompt transcripts; 10 Excel / Microsoft 365 prompts, 150 transcripts; 10 ES round 2 prompts, 150 transcripts; 10 skills in English and Spanish: 180 current skill transcripts, 114 from earlier skill versions, 33 set-aside runs; the same skills in French and Brazilian Portuguese: 180 current transcripts, 45 from earlier versions.

Rounds and dates (UTC, start times of the runs)

• Round 1 — 30 English + 10 Spanish prompts: 2026-10-19 11:34 to 2026-10-19 12:20.
• Round 2 — 20 French + 20 Brazilian Portuguese prompts: 2026-10-19 18:59 to 2026-10-19 20:09.
• Claude Skills round, English and Spanish (current versions): 2026-10-19 14:50 to 2026-10-19 16:13.
• Fable round — claude-fable-5-1 added on the SAME locked material: all 80 prompts of rounds 1 and 2 (240 transcripts) and the current Claude Skills (60 transcripts): 2026-10-20 09:05 to 2026-10-20 10:41.
• Gemini round — gemini-4-argon-medium added on the SAME locked material: all 80 prompts of rounds 1 and 2 (240 transcripts): 2026-10-20 11:16 to 2026-10-20 11:54. Not run on the Claude Skills (a Claude format).
• Excel / Microsoft 365 task round — 10 new prompts (4 English, 2 Spanish, 2 French, 2 Brazilian Portuguese; profession any, tools excel / microsoft-365), all 5 models x 3 runs (150 transcripts): 2026-10-20 12:33 to 2026-10-20 12:43. Text-only answers: formulas were judged by their logic and the stated result on the given data, not executed in Excel. These are chat models answering a pasted task, not Copilot inside Excel or Microsoft 365.
• ES round 2 — 10 new Spanish prompts (separately locked set bench/rubrics.lock-es2.json), all 5 models x 3 runs (150 transcripts, folder prompts-es2/): 2026-10-21 04:38 to 2026-10-21 05:17. Same judges, judge-swap calibration (bench/calibration-es2.json) and spot-check (bench/spotcheck-es2.json) as the other rounds.
• Claude Skills FR/PT round — French (France) and Brazilian Portuguese adaptations of the 10 skills, claude-opus-5-5, claude-sonnet-5, claude-fable-5-1 x 3 runs, graded by gpt-6-astra on rubrics locked separately (skills/_bench/specs-frpt.yaml, skills/_bench/rubrics.lock-frpt.json); current versions: 180 transcripts, 2026-10-21 05:41 to 2026-10-21 09:55. Four adaptations were revised after the first run and re-tested on the same locked input; the earlier texts and their runs are kept as evidence in v1.0/ / v1.1/ folders (construction-daily-report-delay-notice/fr/v1.0, construction-daily-report-delay-notice/fr/v1.1, event-planners-vendor-rfp/fr/v1.0, event-planners-vendor-rfp/pt/v1.0, sales-managers-pipeline-review/fr/v1.0; 45 transcripts). No judge-swap calibration or spot-check was run on this round.

Models

Model id	Provider (as recorded)	Role
claude-opus-5-5	anthropic	tested model; judge of gpt-6-astra outputs
claude-sonnet-5	anthropic	tested model
gpt-6-astra	openai	tested model; judge of Claude outputs (prompts and skills)
claude-fable-5-1	anthropic	tested model (added 2026-10-20, prompts and skills)
gemini-4-argon-medium	google	tested model (added 2026-10-20, prompts only)

Claude and GPT runs were sent through an agent command-line client in safe mode (tools, web access, memory and custom instructions off). The client adds its own generic assistant system instruction, identical for every model. Claude models were reached through a routing service on a subscription, gpt-6-astra through an OpenAI subscription sign-in.

gemini-4-argon-medium was reached through Google's Antigravity command-line agent, not a plain API call. Each run used a custom agent with no tools, skills or rules loaded and a one-line system prompt ("You are a helpful assistant."), started in a fresh empty folder in sandbox mode with permission prompts not auto-approved. The client still wraps the query with the local time and a model-selection note, and it still exposes one built-in tool (listing or stopping background tasks). After each run the client's own log was read: a run with any tool call would not have counted as completed. In this archive: 0 tool calls, 1 turn per run. The agy_usage header line is the token count the client reported. Nothing was edited by hand between the query and the output.

How the rubrics were locked

Before any model saw a prompt, its rubric was written and the SHA-256 of (prompt, input, rubric) was stored in bench/rubrics.lock.json (skills: skills/_bench/rubrics.lock.json, hash of skill, language, input and rubric). The harness refused any run whose hash did not match. Every transcript header carries rubric_sha256; skill transcripts also carry skill_sha256, the hash of the exact SKILL.md text embedded in the query. You can recompute a prompt hash as sha256(json.dumps([prompt, input, rubric], ensure_ascii=False, sort_keys=True)).

How the judging worked

• Cross-family: gpt-6-astra graded Claude outputs and Gemini outputs, claude-opus-5-5 graded gpt-6-astra outputs. The skills round has only Claude models, so all skill runs were graded by gpt-6-astra.
• One strict JSON verdict per criterion (pass/fail + one-line reason); an unsure judge had to mark fail.
• Calibration: a seeded sample of runs was re-graded by the other judge (bench/calibration*.json; the added models have their own files bench/calibration-fable-*.json, bench/calibration-argon-*.json, and the Excel / Microsoft 365 round bench/calibration-tools.json).
• Spot-check: the editor agent operating the bench (an AI agent, not a human) wrote its own verdict from the full transcript before reading the judge's (bench/spotcheck*.json).
• No judge-swap calibration or spot-check was run on the skills rounds (English/Spanish incl. the Fable runs, and French/Portuguese).

What was removed (sanitizing)

Command lines, session and conversation ids, local file paths and run-meta files were removed; provider names are reduced to the vendor (anthropic, openai, google). Queries and outputs are otherwise verbatim.

What a pass does not mean

A pass means an output met these rubric criteria on this fictional input. It is not a professional sign-off, not a test of the consumer apps (ChatGPT, Claude.ai, Copilot), and not a guarantee for other inputs.