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Claude Skills by thedixitjain
github.com/thedixitjain12,707 skills283 installs48,721 views
- Llama Cppllama.cpp local GGUF inference + HF Hub model discovery.Votes: 0GitHub stars: 3
- Llm ConfigConfigure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptationVotes: 0GitHub stars: 3
- Llm Evaluation WshobsonImplement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.Votes: 0GitHub stars: 3
- Llm EvaluationMaster comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.Votes: 0GitHub stars: 3
- Local Llm ExpertMaster local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.Votes: 0GitHub stars: 3
- Long Term Impact EvaluationChoose methods for measuring long-term product impact after or beyond an A/B test. Use when comparing long-term holdbacks, post-period analysis, continuous monitoring, CLV models, delayed effects, short-term versus long-term metric tradeoffs, or lower-cost alternatives to long-term holdbacks.Votes: 0GitHub stars: 3
- Lora Qlora RecipesConfigure LoRA and QLoRA supervised fine-tuning with current best-practice hyperparameters. Use when writing or reviewing a LoRA/QLoRA training configuration, choosing rank/alpha/target modules, or deciding between LoRA, QLoRA, and full fine-tuning.Votes: 0GitHub stars: 3
- Lumen AbtestA/B test design — produce an experiment spec with hypothesis, primary metric, MDE, sample size, run time, and decision rule. Also determines when NOT to A/B test and what to do instead. Use when asked to \"design an A/B test\", \"should we test this\", \"experiment design\", \"how do we know if this works\", \"what's the sample size\", or \"set up an experiment\".Votes: 0GitHub stars: 3
- LumenProduct analyst — metrics architecture, funnel analysis, A/B test design, retention, and growth measurement.Votes: 0GitHub stars: 3
- Machine Learning For HealthUse when targeting Machine Learning for Health (ML4H) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for AI for health.Votes: 0GitHub stars: 3
- Math UnicodeThis skill must be used whenever a response needs mathematical notation — equations, filters, set-builder notation, statistics, calculus, linear algebra, logic, ratios, drops, or counts. Load it before composing, including when the user explicitly mentions math-unicode. Emit terminal-native Unicode inline, never raw LaTeX delimiters or commands.Votes: 0GitHub stars: 3
- Mdr 745 SpecialistEU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Covers Annex VIII classification rules, Annex II/III technical files, Annex XIV clinical evaluation, Art. 86 PSUR schedules, and EUDAMED integration. Use when classifying a medical device under MDR, building or gap-checking a technical file, planning clinical evaluation or PMS/PSUR cadence, or preparing for notified body review (e.g., 'what class i...Votes: 0GitHub stars: 3
- Micro Artifact EvaluationUse when preparing a MICRO artifact for post-acceptance evaluation — packaging simulators, configs, traces, and scripts so evaluators can regenerate the paper's figures, targeting the ACM Available/Functional/Reproducible badges, handling licensed workloads and long simulations, and earning the optional artifact appendix.Votes: 0GitHub stars: 3
- Micro ExperimentsUse when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon, tuning baselines the PC will respect, selecting workload suites, running ablations and sensitivity sweeps, and reporting geomeans with full overhead accounting.Votes: 0GitHub stars: 3
- Mindtickle Core Workflow A'Execute MindTickle primary workflow: Training Content Management. Trigger: \"mindtickle training content management\", \"primary mindtickle workflow\". 'Votes: 0GitHub stars: 3
- Misq MethodsUse when choosing and defending the research design for a MIS Quarterly manuscript — a behavioral survey/experiment, an economics-of-IS identification strategy, a design-science build-and-evaluate cycle, or an organizational/qualitative design. Matches the method to the IS claim and the manuscript category; it designs the study and hands estimation/evaluation to misq-data-analysis.Votes: 0GitHub stars: 3
- Misq RebuttalUse after a MIS Quarterly revision decision to plan the revision and draft the point-by-point response — prioritizing the Senior Editor's letter, addressing tradition-specific rigor concerns (identification, validity/CMB, artifact evaluation, trustworthiness), updating the transparency materials, and keeping the revised manuscript within its page limit. Drafts the response after the manuscript is actually revised; interpret the decision first with misq-review-process.Votes: 0GitHub stars: 3
- Mixed Precision Trainer'Manage mixed precision trainer operations. Auto-activating skill for ML Training. Triggers on: mixed precision trainer, mixed precision trainer Part of the ML Training skill category. Use when working with mixed precision trainer functionality. Trigger with phrases like \"mixed precision trainer\", \"mixed trainer\", \"mixed\". 'Votes: 0GitHub stars: 3
- Ml Adoption PlaybookEnd-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration.Votes: 0GitHub stars: 3
- Ml EngineerBuild production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.Votes: 0GitHub stars: 3
- Ml Experiment EvaluationPlan evaluation strategies for machine-learning product changes. Use when deciding between offline evaluation, interleaving, online A/B tests, multi-armed bandits, or model filtering for ranking, recommendation, search, personalization, or other ML-powered user experiences.Votes: 0GitHub stars: 3
- Mlflow Tracking Setup'Configure mlflow tracking setup operations. Auto-activating skill for ML Training. Triggers on: mlflow tracking setup, mlflow tracking setup Part of the ML Training skill category. Use when working with mlflow tracking setup functionality. Trigger with phrases like \"mlflow tracking setup\", \"mlflow setup\", \"mlflow\". 'Votes: 0GitHub stars: 3
- Mlsys Artifact EvaluationUse when packaging an accepted MLSys paper's code, configs, and measurement scripts for the venue's post-acceptance artifact evaluation, targeting the Availability, Functional, and Reproducible badges, writing the Artifact Appendix, handling hardware that AE reviewers cannot access, and answering anonymous evaluator questions.Votes: 0GitHub stars: 3
- Mobicom Artifact EvaluationUse when packaging a MobiCom artifact for the evaluation committee — choosing among the three ACM badges as a calibration of what you can prove, building a hardware-optional reproduction path for evaluators without radios, writing the smoke run that establishes functionality, and making code, data, and traces available.Votes: 0GitHub stars: 3
- Mobisys Artifact EvaluationUse when packaging a MobiSys artifact for the Artifact Evaluation Committee — choosing among the three independent ACM badges (Available, Evaluated–Functional, Results Reproduced), building the workflow scripts the single-blind AEC runs on its own machines, and providing a hardware-optional path for evaluators who lack the exact phone, wearable, or board.Votes: 0GitHub stars: 3
- Mobisys WorkflowUse when planning a MobiSys project timeline backward from the single early-December paper deadline through registration, two-round review with an early-reject cut, the rebuttal, notification, artifact evaluation, camera-ready, and the June conference — with device-experiment lead time built in and the one-deadline-per-year risk made explicit.Votes: 0GitHub stars: 3
- ModalModal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.Votes: 0GitHub stars: 3
- Model Checkpoint Manager'Manage model checkpoint manager operations. Auto-activating skill for ML Training. Triggers on: model checkpoint manager, model checkpoint manager Part of the ML Training skill category. Use when working with model checkpoint manager functionality. Trigger with phrases like \"model checkpoint manager\", \"model manager\", \"model\". 'Votes: 0GitHub stars: 3
- Model Evaluation Metrics'Build model evaluation metrics operations. Auto-activating skill for ML Training. Triggers on: model evaluation metrics, model evaluation metrics Part of the ML Training skill category. Use when working with model evaluation metrics functionality. Trigger with phrases like \"model evaluation metrics\", \"model metrics\", \"model\". 'Votes: 0GitHub stars: 3
- Model Explainability Tool'Build model explainability tool operations. Auto-activating skill for ML Training. Triggers on: model explainability tool, model explainability tool Part of the ML Training skill category. Use when working with model explainability tool functionality. Trigger with phrases like \"model explainability tool\", \"model tool\", \"model\". 'Votes: 0GitHub stars: 3
- Model Quantization Tool'Build model quantization tool operations. Auto-activating skill for ML Deployment. Triggers on: model quantization tool, model quantization tool Part of the ML Deployment skill category. Use when working with model quantization tool functionality. Trigger with phrases like \"model quantization tool\", \"model tool\", \"model\". 'Votes: 0GitHub stars: 3
- Molcell Star MethodsUse to build Molecular Cell's mandatory STAR Methods — the Key Resources Table, the Resource Availability subsections, Experimental Model and Subject Details, Method Details, and Quantification and Statistical Analysis, in the required order and with the reagent transparency Molecular Cell reviewers demand.Votes: 0GitHub stars: 3
- Monte Carlo Validation NotebookGenerates SQL validation notebooks for dbt PR changes with before/after comparison queries.Votes: 0GitHub stars: 3
- Mortgage Loan OfficerGuides borrowers through mortgage refinance evaluation — collects loan data, extracts mortgage statement fields, evaluates qualification, and delivers recommendations with consumer-friendly communication.Votes: 0GitHub stars: 3
- Naacl Artifact EvaluationUse when packaging datasets, models, prompts, or annotation materials for a NAACL-bound submission — building the artifact around the Responsible NLP checklist's artifact questions, documenting provenance and licensing for language data, and handling community-owned or Indigenous-language resources correctly.Votes: 0GitHub stars: 3
- Ndss Artifact EvaluationUse when preparing an NDSS artifact for evaluation after conditional acceptance — targeting the Available, Functional, and Reproduced badges, packaging attacks and measurements responsibly, writing the 2-page artifact appendix, and handling dangerous or embargoed material.Votes: 0GitHub stars: 3
- Nejm RebuttalUse after NEJM reviews arrive — often including a dedicated statistical reviewer and an editor letter — to triage the decision, answer statistical comments rigorously, and draft a point-by-point response that quotes each comment, the response, and the revised manuscript text. Do not run before the main text is actually revised.Votes: 0GitHub stars: 3
- Nejm StatisticsUse to enforce NEJM's clinical statistical reporting — confidence intervals over bare P values, the pre-specified intention-to-treat primary analysis, multiplicity control for secondary endpoints, pre-specified subgroups with interaction tests, missing-data handling, and absolute risk with NNT alongside relative measures.Votes: 0GitHub stars: 3
- Nejm SubmissionUse as the final preflight before submitting to NEJM — a complete clinical checklist across significance, registration, reporting guidelines, abstract, statistics, display items, ethics, references, and required files. Bundles a checklist and a clinical cover-letter template.Votes: 0GitHub stars: 3
- Nemo CuratorCurate LLM training data: dedupe, filter, PII redaction.Votes: 0GitHub stars: 3
- NetworkxCreate, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.Votes: 0GitHub stars: 3
- Neural Training> Neural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.Votes: 0GitHub stars: 3
- Neurips Artifact EvaluationUse when packaging NeurIPS code, data, models, demos, benchmarks, or other research artifacts for anonymous review, reproducibility, public release, or MLRC-style artifact scrutiny.Votes: 0GitHub stars: 3
- Nsdi Artifact EvaluationUse when preparing an accepted NSDI paper's artifact for badge evaluation — packaging code, traces, and testbed recipes for the AEC, choosing which badges to pursue, meeting Zenodo-style permanence expectations, and timing public release to stay eligible for the Community Award.Votes: 0GitHub stars: 3
- Nsdi WorkflowUse when planning an NSDI campaign across the spring and fall deadlines — sequencing abstract and paper gates, notification waits, one-shot revision windows, artifact evaluation, and the May symposium — so a networked-systems project always knows which of the two yearly gates it is really building toward.Votes: 0GitHub stars: 3
- Nw Ddd StrategicStrategic DDD — bounded context discovery, context mapping patterns, subdomain classification, ubiquitous language, and organizational alignmentVotes: 0GitHub stars: 3
- Nw Der Review CriteriaEvaluation criteria and scoring for data engineering artifact reviewsVotes: 0GitHub stars: 3
- Nw DivergeGenerates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence. Use when the team has a validated problem but hasn't chosen a solution approach.Votes: 0GitHub stars: 3
- Nw Jtbd Workflow SelectionJTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipesVotes: 0GitHub stars: 3
- Nw Taste EvaluationDesign taste evaluation framework — DVF primary filter, Apple/Google/Jobs design principles as explicit scoring criteria, weighted decision matrix, and option ranking for the DIVERGE waveVotes: 0GitHub stars: 3