AI Transparency Statement¶
This page is generated from
PROMPT_LOG.mdbyscripts/generate_ai_transparency.py. It reports the development requests recorded in the repository; it does not measure scientific validity or assign code authorship.
Summary¶
From 2026-03-21 through 2026-08-17, the log contains 118 prompts totaling 27,743 words. The median prompt contains 32 words and the mean contains 235.1 words. Under the published keyword rules, the most common primary topic is QA and visualization, and the most common request intent is Implementation or modification.
Which AI was used¶
The prompt log declares the AI system used for logged work. Model names are reported only when an entry records them; missing model metadata is not inferred.
| AI system | Logged prompts |
|---|---|
| OpenAI Codex | 118 |
| Model metadata | Logged prompts |
|---|---|
| Not recorded | 106 |
| GPT-5 family (exact deployment identifier not exposed) | 7 |
| GPT-5 | 5 |
Model metadata is recorded for 12 of 118 entries (10.2%).
How AI was used¶
The logged requests cover implementation and modification, audits and investigations, verification, documentation, QA, pipeline behavior, and publication maintenance. Each entry receives one primary topic and one primary intent through deterministic keyword scoring over the prompt and its logged task label. These labels summarize requests, not completed work; consult Git history, tests, and review records for evidence of outcomes.
Scope and limitations¶
- The source log begins after repository development was already underway, so it is not a complete history of AI use.
- It records user prompts, not assistant responses, accepted/rejected suggestions, token usage, elapsed time, or line-level authorship.
- Long prompts may contain pasted logs or specifications; word counts measure prompt text, not effort.
- Topic and intent labels are rule-based approximations based on prompt text and the logged task label. The rules are version-controlled in the generator.
- Legacy entries use the log-level AI-system default. Their model is
Not recordedunless an entry explicitly provides model metadata. - Prompts may contain sensitive material. The generated report includes aggregates only and does not reproduce prompt text.
Reproduce this statement¶
python scripts/generate_ai_transparency.py
python scripts/generate_ai_transparency.py --check
Machine-readable statistics are available in ai-transparency.json. The source-log SHA-256 recorded there allows a reviewer to verify which prompt-log revision produced this page.