Plugins
12 plugins@samyakjhaveri
Research
Research from SamyakJhaveri/loam.
18 skills · plugin
@brycewang-stanford
Auto Empirical Research Skills
Auto Empirical Research Skills from brycewang-stanford/Auto-Empirical-Research-Skills.
86 skills · plugin
curated
Deep Research Report
For analysts and researchers needing comprehensive, evidence-backed reports with citations.
11 skills · plugin
@phuryn
Market Research
Market research skills for PMs: user personas, market segmentation, sentiment analysis, and competitive analysis.
7 skills · plugin
@owl-listener
Design Research
User research skills for designers: personas, empathy maps, journey maps, interview scripts, usability testing, and card sorting.
12 skills · plugin
@alirezarezvani
Research Ops
Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork) + clinical-research (study design: protocol synopsis + endpoint selection + sample-size/power for means/proportions/survival + phase-gate feasibility) + research-finance (R&D program budgeting with F&A split + burn/runway + capital
5 skills · plugin
curated
Market Research Report
Install this pack to produce a decision-oriented market research report with competitive analysis, market sizing, and source attribution.
7 skills · plugin
curated
Company Research Profile
Install this pack to build and manage a company research profile with fundamentals, valuation bands, red flags, and events.
4 skills · plugin
curated
User Persona from Research
Install this pack to create detailed, actionable user personas from research data with jobs-to-be-done and behavioral insights.
5 skills · plugin
@testdouble
Han Research
Pre-planning knowledge-work skills for the Han suite: understanding a problem before anyone commits to a plan. Home of research, gap-analysis, and issue-triage, plus the research-analyst agent. Depends on han-communication and han-core; bundled by the han meta-plugin.
3 skills · plugin
@brycewang-stanford
25 HosungYou Diverga
25 HosungYou Diverga from brycewang-stanford/Auto-Empirical-Research-Skills.
32 skills · plugin
@brycewang-stanford
42 Wanshuiyin ARIS
42 Wanshuiyin ARIS from brycewang-stanford/Auto-Empirical-Research-Skills.
38 skills · plugin
Results for “research”
266 skillsPaw Wbc Agent Producer
Structured producer who turns research insights into production-ready slide deck outlines and scripts. Triggers: 'create slides', 'write webinar script', 'build slide deck', 'webinar outline', 'produce webinar', or when user asks for the Producer.
85 · bundle
Audiocraft Audio Generation
Generate music and sound effects from text descriptions using Meta's AudioCraft library, with support for melody conditioning, stereo output, and style transfer.
10.4k · bundle
Nemo Guardrails
Add programmable safety guardrails to LLM applications at runtime, including jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, and toxicity detection.
10.4k
Model Merging
Merge multiple fine-tuned models using mergekit to combine capabilities without retraining, covering SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.
10.4k · bundle
Constitutional AI
Train AI models to be harmless through self-critique and AI feedback using a set of constitutional principles, without requiring human labels for harmful outputs.
10.4k
Pytorch Lightning
Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.
10.4k · bundle
Dmux Workflows
Orchestrates parallel AI agent sessions using dmux, a tmux pane manager, with patterns for research, implementation, testing, and code review across multiple harnesses.
0
Huggingface Papers
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page.
10.8k
Google Maps Reviews API Skill
Extract structured review data from Google Maps search results using the BrowserAct API, enabling local business analysis, reputation monitoring, and competitive benchmarking.
3.7k · bundle
Amazon Best Selling Products Finder API Skill
Extract structured best-selling product data from Amazon, including titles, prices, ratings, reviews, sales volume, and promotions, using the BrowserAct API.
3.7k · bundle
Qdrant Vector Search
Build production RAG and semantic search systems with a high-performance vector database written in Rust, supporting hybrid search, filtering, and horizontal scaling.
10.4k · bundle
Hqq Quantization
Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends for deployment with vLLM or HuggingFace Transformers.
10.4k · bundle
Verl Rl Training
Train LLMs with reinforcement learning using verl (Volcano Engine RL), supporting RLHF, GRPO, PPO, and other algorithms for scalable post-training with flexible infrastructure backends.
10.4k · bundle
Nemo Evaluator Sdk
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution on local Docker, Slurm HPC, or cloud platforms.
10.4k · bundle
Distributed LLM Pretraining Torchtitan
Pretrains large language models from scratch using PyTorch-native distributed training with 4D parallelism (FSDP2, TP, PP, CP) and Float8 support on H100 GPUs.
10.4k · bundle
User Segmentation
Analyze diverse user feedback to identify at least 3 distinct behavioral and needs-based user segments based on jobs-to-be-done, behaviors, and motivations.
22.6k
Llava
Enables visual instruction tuning and image-based conversations using open-source vision-language models. Supports multi-turn image chat, visual question answering, and image understanding tasks.
10.4k · bundle
Stable Diffusion Image Generation
Generate images from text prompts, perform image-to-image translation, inpainting, and build custom diffusion pipelines using Stable Diffusion models via HuggingFace Diffusers.
10.4k · bundle
Knowledge Distillation
Compress large language models using knowledge distillation from teacher to student models, covering temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.
10.4k · bundle
A5
Agent A5 - Paradigm & Worldview Advisor - Philosophical foundations for research design. Covers ontology, epistemology, axiology, and methodology alignment. Use when: establishing philosophical foundations, justifying methodological choices, writing positionality statements Triggers: paradigm, 패러다임, ontology, epistemology, worldview, 세계관, philosophical foundations, 철학적 기초
1k
Gptq
Quantize large language models to 4-bit with minimal accuracy loss using GPTQ, enabling deployment of 70B+ models on consumer GPUs with 4× memory reduction and 3-4× faster inference.
10.4k · bundle
Sentence Transformers
Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.
10.4k · bundle
Stata Toolkit
Activate when users mention Stata commands, .do files, regressions, econometrics, stored results, graphs, dataset inspection, replication, or Stata errors. Route the task through mcp-stata tools and the specialized research skills instead of treating it as plain text coding.
1k · bundle
Nemo Rl Auto Research
Guides agents through the full lifecycle of NeMo-RL experiments: understanding recipes, launching reproducible runs, analyzing results, and preserving human oversight with git and TSV logs.
2.2k · bundle
Nemo Curator
GPU-accelerated data curation for LLM training, supporting text, image, video, and audio with fuzzy deduplication, quality filtering, semantic deduplication, PII redaction, and NSFW detection.
10.4k · bundle
Ml Training Recipes
Provides battle-tested PyTorch training recipes for LLMs, vision, diffusion, and biomedical domains, covering training loops, optimizer selection, LR scheduling, mixed precision, and debugging.
10.4k · bundle
Model Pruning
Compress large language models by 40-60% with minimal accuracy loss using one-shot pruning techniques like Wanda and SparseGPT, enabling faster inference and deployment on constrained hardware.
10.4k · bundle
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
2
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
1
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
1
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
1
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
0
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
1
Agents Md
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
1
Auto Review Loop
Autonomous multi-round research review loop. Repeatedly reviews via Codex MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
1k
Serving Llms Vllm
Deploy and serve LLMs with high throughput using vLLM's PagedAttention and continuous batching. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism for production inference.
10.4k · bundle