Results for “prismic”
23 skillspymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
0 · bundle
pymoo
Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.
253 · bundle
pymoo
Solve single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including Pareto front analysis, constraint handling, and benchmarking on standard test problems.
3 · bundle
pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
3 · bundle
shenmo-skill
沈墨(悬疑剧虚构)认知与表达框架(压缩蒸馏):创伤反杀叙事、时代灰雾、钢琴意象 触发:漫长的季节 等。虚构;禁止犯罪模仿
9 · bundle
pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
2 · bundle
pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
5 · bundle
pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
0 · bundle
perspective-framing
当需要在写作中与读者建立情感连接、放大问题严重性,并引出后续解决方案时
11 · bundle
pymoo
Framework de otimização multi-objetivo. NSGA-II, NSGA-III, MOEA/D, frentes de Pareto, tratamento de restrições, benchmarks (ZDT, DTLZ), para problemas de design e otimização em engenharia.
10 · bundle
gemini-api-dev
Build applications with Gemini API hosted models, including Gemini and Gemma 4, using multimodal content, function calling, structured outputs, and current SDKs for Python, JavaScript, Go, and Java.
3.8k
pyopenms
Analyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.
30.2k · bundle
dmaic
>- DMAIC (Define-Measure-Analyze-Improve-Control) — Six Sigma structured problem-solving for chronic, data-driven quality improvement projects. Use when a problem recurs despite corrective actions, when a process needs systematic capability improvement, or when a customer requests a Six Sigma approach. Use 8D for reactive single-incident problems; use DMAIC for recurring systemic issues requiring statistical analysis. Covers IATF 16949 §10.1 and ISO 9001 §10.3.
2 · bundle
alimask
Use when masking columns or coordinate ranges in multiple-sequence alignments before downstream HMMER or alignment-processing steps.
0 · bundle
hunting-for-lateral-movement-via-wmi
Detect WMI-based lateral movement by analyzing Windows Event ID 4688 process creation and Sysmon Event ID 1 for WmiPrvSE.exe child process patterns, remote process execution, and WMI event subscription persistence.
24.6k · bundle
matchms
Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.
30.2k · bundle
misaka-skill
御坂美琴(少年漫)认知与表达框架(压缩蒸馏):炮姐傲娇、正义感、学园都市梗 触发:某科学的超电磁炮 等。虚构
9 · bundle
matchms
Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.
5 · bundle
minglou-skill
明楼(谍战虚构)认知与表达框架(压缩蒸馏):三面间谍、辞令层叠、亲情作人质 触发:伪装者 等。禁止间谍违法教程
9 · bundle
project-session-manager
Worktree-first dev environment manager for issues, PRs, and features with optional tmux sessions
1 · bundle
matchms
Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.
3 · bundle
first-principles-thinking
Socratic coach for breaking down problems to fundamental truths. Use when users want to think through a problem deeply, challenge assumptions, or find innovative solutions. Triggers on requests like "help me think through this", "let's break this down", "what are my blind spots", "I'm stuck on a problem", "challenge my assumptions", or explicit requests for first-principles thinking.
3 · bundle
pyopenms
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
5 · bundle