theory-sharpen

Solid

Systematically assess whether a paper's theoretical results can be strengthened: relax assumptions, sharpen rates, align theory with model and experiments, and benchmark against state-of-the-art literature. Use when user says "sharpen theory", "strengthen results", "relax assumptions", "improve rates", "理论提升", "放宽假设", "优化rate", "theory alignment", "理论对齐", or wants to go beyond proof correctness toward theoretical optimality and practical relevance.

AI & Automation 7 stars 2 forks Updated today MIT

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Quality Score: 84/100

Stars 20%
30
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Theory-Sharpen — Systematic Theoretical Improvement Assessment > 🔬 **Model Recommendation**: Run this skill on **Claude Opus** for best results. > Framework classification, assumption-relaxation analysis, and rate-sharpening all > require deep mathematical reasoning. If your session is not on Opus, run > `/model opus` before invoking. Literature search and Codex cross-review will use > Opus sub-agents. Go beyond "is the proof correct?" to ask "can the theory be stronger, sharper, and better aligned with the model, the literature, and the experiments?" **Pipeline position**: ``` /proofcheck → /proof-repair → /theory-sharpen → /proof-writer Correct? Fix issues Improve theory Write new proofs ``` This skill can also run standalone on any paper with theoretical results. ## Context: $ARGUMENTS --- ## Core Philosophy A good theory paper is evaluated on three axes: 1. **Strength**: Are assumptions as weak as possible? Are rates as sharp as possible? 2. **Alignment**: Does the theory match what the model actually provides and what the experiments actually test? 3. **Positioning**: How does the result compare to the best known results in the literature? This skill systematically audits all three axes and produces an actionable improvement roadmap. --- ## Step 0: Ingest & Map the Theory-Model-Experiment Triangle ### 0A: Locate Inputs Parse `$ARGUMENTS`. Accept: - A `.tex` file path → read directly - A paper directory → read `paper.tex` + any `/proof...

Details

Author
gyf9712
Repository
gyf9712/stat-theory-skills
Created
2 months ago
Last Updated
today
Language
Python
License
MIT

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