Imported from yiqunchen/LLM-smoking-cessation (
AGENTS.md). Install upstream withnpx skills add yiqunchen/LLM-smoking-cessation. Copyright stays with the author.
Working in this repository
- dt10 only. Every result, table, and figure uses the splits in
data/splits/canonical/(docs/DATA_POLICY.md). The retired 70/30-era splits and results exist only in gitignoredarchive/; never use them. - Three outcomes: content, coping, quitting. The raw
designrating is never analysed or reported. - No placeholders. Never fabricate or ship mock, preview, or partial results as complete. If something is missing, say so and give the rerun command.
- Never delete result data. Result JSONs are expensive API runs. Move
things to
archive/if they must leave the tree. - Validate before analysing:
analysis/verify_prompt_ablations.pyandanalysis/audit_prompt_ablations.pyfor prompt ablations;analysis/verify_dt10_artifacts.pyfor the main dt10 outputs.
Conventions
uv sync; run with.venv/bin/python(Python 3.12). All LLM calls go through OpenRouter (OPENROUTER_API_KEY).- Long runs go in tmux and are checkpointed;
scripts/run_prompt_ablations.shresumes and skips completed conditions. Result JSONs are{row_index: record}keyed by canonical test-row index;manifest_dt10_k7.jsonrecords split SHA-256s and per-condition run settings. - Figures: bold Helvetica (Arial, DejaVu Sans fallbacks), white background,
light gray grid, PNG + PDF. Model colors: GPT-4o-mini
#0173B2, GPT-5#DE8F05, DeepSeek-R1#029E73, Grok#CC78BC, Gemini-2.5-Pro#CA9161, Logistic Regression#E02020, Random Forest#7F7F7F; reference gray#4D4D4D. - Commit result data with the code that produced it.