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math-review
Verifies math-heavy code for algorithmic correctness and numerical stability. Use when reviewing scientific algorithms, ML models, or numerical code.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Verifies math-heavy code for algorithmic correctness and numerical stability. Use when reviewing scientific algorithms, ML models, or numerical code.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
根据用户说明生成物理/数学教学插图的 AI 绘图提示词。涵盖模型示意图、函数曲线图等,支持多面板组合布局。
跨文件代码审查,检查 Typst 代码的一致性、可维护性和内容职责原则遵循情况
扫描 Typst 文件中的标签(如 <def:limit-of-sequence-of-sets>),在 Appendix 的 Glossary 节中生成字母索引。
审查数学证明的逻辑完整性、符号一致性和推理严密性
本技能文件规定了 `TypstTemplate/math-notes.typ` 模板的使用方式和所有可用组件。
本技能文件规定了如何编译验证 Typst 文件,确保修改后的笔记可以正确生成 PDF。
| name | math-review |
| description | Verifies math-heavy code for algorithmic correctness and numerical stability. Use when reviewing scientific algorithms, ML models, or numerical code. |
| alwaysApply | false |
| category | specialized |
| tags | ["math","algorithms","numerical","stability","verification","scientific"] |
| tools | [] |
| usage_patterns | ["algorithm-review","numerical-analysis","derivation-verification","stability-assessment"] |
| complexity | advanced |
| model_hint | deep |
| estimated_tokens | 200 |
| progressive_loading | true |
| dependencies | ["pensive:shared","imbue:proof-of-work","imbue:review-core","imbue:structured-output"] |
Intensive analysis ensuring numerical stability and alignment with standards.
/math-review
Verification: Run the command with --help flag to verify availability.
math-review:context-syncedmath-review:requirements-mappedmath-review:derivations-verifiedmath-review:stability-assessedmath-review:evidence-loggedmath-review:findings-verifiedpwd && git status -sb && git diff --stat origin/main..HEAD
Verification: Run git status to confirm working tree state.
Enumerate math-heavy files (source, tests, docs, notebooks). Classify risk: safety-critical, financial, ML fairness.
Translate requirements → mathematical invariants. Document pre/post conditions, conservation laws, bounds. Load: modules/requirements-mapping.md
Re-derive formulas using CAS. Challenge approximations. Cite authoritative standards (NASA-STD-7009, ASME VVUQ). Load: modules/derivation-verification.md
Evaluate conditioning, precision, scaling, randomness. Compare complexity. Quantify uncertainty. Load: modules/numerical-stability.md
pytest tests/math/ --benchmark
jupyter nbconvert --execute derivation.ipynb
Verification: Run pytest -v tests/math/ to verify.
Log deviations, recommend: Approve / Approve with actions / Block. Load: modules/testing-strategies.md
math-review:findings-verified)Every issue must cite a real location and a verbatim anchor. Write
findings to .review/findings.json and confirm each citation resolves:
python plugins/imbue/scripts/citation_verifier.py \
--findings .review/findings.json --repo-root .
Drop or label UNVERIFIED any finding the verifier fails (exit 1);
only verified findings enter the report. See Skill(imbue:review-core)
Step 5 for the protocol and Skill(imbue:structured-output) for the
finding schema.
Default (200 tokens): Core workflow, checklists +Requirements (+300 tokens): Invariants, pre/post conditions, coverage analysis +Derivation (+350 tokens): CAS verification, standards, citations +Stability (+400 tokens): Numerical properties, precision, complexity +Testing (+350 tokens): Edge cases, benchmarks, reproducibility
Total with all modules: ~1600 tokens
Correctness: Formulas match spec | Edge cases handled | Units consistent | Domain enforced Stability: Condition number OK | Precision sufficient | No cancellation | Overflow prevented Verification: Derivations documented | References cited | Tests cover invariants | Benchmarks reproducible Documentation: Assumptions stated | Limitations documented | Error bounds specified | References linked
## Summary
[Brief findings]
## Context
Files | Risk classification | Standards
## Requirements Analysis
| Invariant | Verified | Evidence |
## Derivation Review
[Status and conflicts]
## Stability Analysis
Condition number | Precision | Risks
## Issues
[M1] [Title]
- Location: file.py:123
- Anchor: `verbatim source text at line 123`
- Issue: [what is wrong] | Fix: [remediation] | Evidence: [E1]
## Recommendation
Approve / Approve with actions / Block
Every issue's Anchor is the exact source text at Location; it is what
citation_verifier.py re-reads to prove the finding is real.
Verification: Run the command with --help flag to verify availability.
Location + verbatim Anchor, and citation_verifier.py confirmed all citations (exit 0) or unverified issues were dropped or labeled UNVERIFIED