ccf-experiment-designer

name	ccf-experiment-designer
description	Design CCF paper evidence packages: datasets, baselines, metrics, ablations, robustness tests, result-table templates, and real-result figure/table presentation. Use for experiment design, benchmark planning, baseline selection, ablation design, result tables, publication figures from supplied numbers, 设计实验, 对比实验, 消融, 结果图表. Do not invent results.
metadata	{"ccf_skill_controls":{"handoff_question_mode":"partial","respect_session_denylists":true,"protect_idea_scope_in_writing":true,"private_material_safety":"moderate","shared_controls":"../ccf-common/references/"}}

CCF Experiment Designer

Core Rule

Design experiments that test the paper's central claims. Build result tables and evidence-bound figure specs only from supplied real values or explicit placeholders. Never fabricate numbers, improvements, significance, benchmark ranks, or user-study outcomes. Publication-grade layout, palette, caption placement, and render QA belong to ccf-visual-composer. Follow the user's requested output shape: experiment plan, table, LaTeX table, figure spec, ablation list, or execution queue.

Modes

• design: datasets, baselines, metrics, ablations, robustness, efficiency, failure analysis, and execution priority.
• result-template: fill-in tables with TBD placeholders.
• result-presentation: result tables, figure evidence plans, chart specs, caption facts, and missing-value markers from supplied real results.

Workflow

1. Identify target venue, paper type, central claims, available results, and whether the task is planning or presenting results.
2. Extract the storyline from the idea or draft. Use ../ccf-paper-writer/references/storyline-blueprint.md only as a schema, not as a writing handoff.
3. Map every major claim to required evidence, reviewer question, dataset/workload, baseline, metric, ablation, and robustness/failure test.
4. If datasets or baselines are unknown, use public-safe search or hand off to ccf-literature-searcher; mark uncertainty instead of guessing.
5. Load references/evidence-design.md for venue-family expectations and references/result-templates.md for result tables.
6. For result presentation, preserve units, seeds, confidence intervals, dataset names, and metric direction. Mark missing values explicitly.
7. Hand off to ccf-visual-composer for publication-grade figure/table layout, palettes, panel maps, captions, manuscript integration, and render QA.
8. Hand off to ccf-paper-writer for manuscript prose, ccf-integrity-auditor for number/claim consistency, and ccf-submission-checker for package or artifact readiness.

Adaptive Output Contract

Return the requested artifact first. For a result table request, output the table. For a figure request, output the evidence-bound figure spec and caption facts, then name ccf-visual-composer as next owner for visual composition when needed. For a full experiment-design request, use this default structure:

Mode:
Venue and assumptions:
Claim-evidence matrix:
Dataset / benchmark needs:
Baseline matrix:
Main experiments:
Ablations:
Robustness / failure / efficiency:
Result tables or figure specs:
Missing values:
Execution priority:
No-fabrication status:
Next CCFA owner:

References

• references/evidence-design.md: experiment and benchmark design.
• references/result-templates.md: fill-in result tables and presentation scaffolds.