science-superpowers
Computational-science methodology for Claude Code: research framing, pre-registration, reproducible analysis, anomaly investigation, and red-team review
Pacote de plugins · de K-Dense, Inc.
Resumo
science-superpowers é um pacote de plugins para ferramentas de programação com IA publicado por K-Dense, Inc.. Marketplaces que lemos e que o listam: 1 (Community GitHub marketplaces). Vimos pela primeira vez em 2026-10-24 e não registramos mudanças desde então. Conforme nossa passagem pelos marketplaces em 2026-10-29.
O que pede
- Instala-se como pacote de plugins
- Hooks declarados: 1
O que declara, pede e executa, por completo
Instale apenas plugins de desenvolvedores em quem você confia. Mostramos o que os marketplaces publicam e não testamos plugins.
Funciona com
- Claude Code
Pelos marketplaces que o listam e pelo transporte MCP que declara, conforme cada cliente documenta. Não testamos plugins.
Conectar
Comandos e configurações gerados apenas a partir do que os marketplaces declaram. Não os executamos por você e não testamos plugins.
Como plugin do Claude Code
Gerado a partir do que Community GitHub marketplaces declara.
/plugin marketplace add k-dense-ai/science-superpowers
/plugin install science-superpowers@science-superpowers-devOnde está publicado
| Marketplace | Status | Versão | Números | Verificado | Visto pela primeira vez |
|---|---|---|---|---|---|
| Marketplace da comunidade k-dense-ai/science-superpowers (Abrir o código no GitHub) | Listado | 0.1.0 | Forks (GitHub): 38 Estrelas (GitHub): 363 |
Sem marcação |
Cada número é do próprio marketplace e nunca é somado entre marketplaces. Um marketplace que não publica números não mostra nenhum: sem número não é zero.
Listado em um marketplace da comunidade
| Marketplace | Repositório | Estrelas (GitHub) |
|---|---|---|
| science-superpowers-dev | k-dense-ai/science-superpowers | 363 |
O que o pacote contém
Conforme publicado em Community GitHub marketplaces.
Skills: 16
designing-the-analysisdispatching-parallel-investigationsestablishing-feasibility-firstexecuting-analysisframing-research-questionsinvestigating-anomalous-resultspreregistering-analysisreceiving-critical-reviewreporting-and-archiving-findingsrequesting-red-team-reviewsetting-up-reproducible-analysissubagent-driven-analysis
Mostrar mais 4
surveying-prior-workusing-science-superpowersverifying-results-before-claimingwriting-science-skills
Hooks: 1
SessionStart
O que mudou
- Passou a ser um produto que acompanhamos
- Community GitHub marketplaces: apareceu
Plugins semelhantes
Produtos cujos próprios nomes, descrições, ferramentas e skills são os mais próximos deste pelo significado, em todos os marketplaces que lemos. A proximidade é ordenada apenas dentro desta lista.
-
Autonomous experimentation skill — your AI coding agent designs experiments, tests hypotheses, discards failures, keeps wins.
-
Reviewable ML research: literature, planning, methodology review, bounded runs, sweeps, implementation verification, ablations, retrospectives, Kaggle, and setup
-
ideation-and-design
Hypothesis generation, experimental design, statistics planning, validation.
-
About Comprehensive research co-pilot for Claude Code and claude.ai — 13 skills covering literature review, methodology, ethics review, data analysis, qualitative coding…
-
The full social-science research pipeline as skills: idea formalization, systematic literature review, theory and hypotheses, research design with power analysis, causal…
-
data-scientist
Use for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research…
-
Drop-in agentic loop skills (autoresearch, literature & writing, data, optimization, red-team, power analysis). Skills install namespaced as agent-loops:<name>.
-
research-methodology
Plan, conduct, evaluate, and synthesize rigorous research investigations with credible evidence and a traceable method, including source-to-claim closure for media evidence. Do…
-
Semi-automated research assistant with skills for literature review, experiments, analysis, writing, and project knowledge management
-
claudecode-research-harness-workflow
Research Agent Harness — a controlled execution environment for reproducible empirical research agents.
Plugins semelhantes por marketplace
A mesma pergunta feita a cada marketplace separadamente: existe lá um equivalente deste plugin?
Listado em Claude Code: claude-plugins-community (5)
-
About Comprehensive research co-pilot for Claude Code and claude.ai — 13 skills covering literature review, methodology, ethics review, data analysis, qualitative coding…
-
A causal inference plugin for AI agents. Describe a problem in plain language and it helps you choose a method, check assumptions, write the analysis in R or Python, and…
-
197 ready-to-use life sciences skills that turn Claude into a domain expert for genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing…
-
Principles and rules for writing faithful scientific code. Scientific code serves truth, not users. This plugin teaches Claude the fundamental differences between scientific and…
-
Research sprint orchestrator for Claude Code. Ask a question, get a decision-ready brief — every finding is tracked as a typed claim, adversarially challenged, confidence-graded…
Listado em Claude Code: claude-plugins-official (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Superpowers teaches Claude brainstorming, subagent driven development with built in code review, systematic debugging, and red/green TDD. Additionally, it teaches Claude how to…
-
Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered…
-
Output.ai workflow development toolkit for Claude Code. Adds 5 specialist agents (planner, builder, debugger, prompt writer, quality reviewer), 40+ slash-command skills covering…
Listado em Claude: knowledge-work-plugins (5)
-
Connect to preclinical research tools and databases (literature search, genomics analysis, target prioritization) to accelerate early-stage life sciences R&D
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Write SQL, explore datasets, and generate insights faster. Build visualizations and dashboards, and turn raw data into clear stories for stakeholders.
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
Listado em Codex: openai-curated (openai/plugins) (5)
-
General life-sciences research workflows with query routing, evidence synthesis, and optional parallel subagent analysis across genetics, omics, biology, chemistry, structure…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Answer product and business questions with data
-
Predict structures, screen molecules and proteins, and design binders.
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
Listado em Community GitHub marketplaces (5)
-
Autonomous experimentation skill — your AI coding agent designs experiments, tests hypotheses, discards failures, keeps wins.
-
Reviewable ML research: literature, planning, methodology review, bounded runs, sweeps, implementation verification, ablations, retrospectives, Kaggle, and setup
-
ideation-and-design
Hypothesis generation, experimental design, statistics planning, validation.
-
The full social-science research pipeline as skills: idea formalization, systematic literature review, theory and hypotheses, research design with power analysis, causal…
-
data-scientist
Use for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research…
Listado em Copilot CLI: github/awesome-copilot (5)
-
Three-layer verification pipeline for AI output. Extracts claims, finds sources, and flags hallucination risks so humans can verify before acting.
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Turn your Copilot sessions into proof of impact — research-grounded HTML reports with effort estimation, skills analysis, and ROI metrics from local session logs.
-
Goal-driven task orchestration with independent verification. Interviews the user to define a clear goal, then loops between a Builder subagent (does the work) and an Inspector…
Listado em Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
-
Advanced Security plugin for GitHub Copilot.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
Listado em Cursor: cursor/plugins (5)
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Track AI visibility, sentiment, and citations.
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
-
Ask Databricks Genie questions about your workspace's data in plain language.
-
Incremental transcript-driven memory updates for AGENTS.md using high-signal bullet points only.
Listado em Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Real-time web search, reasoning, and research through Perplexity's API
-
Sequential Thinking (Reference)
Dynamic and reflective problem-solving through thought sequences.
-
Tools for interacting with Hugging Face models, datasets, research papers, and more.
-
Connect your chat repl to wolfram alpha computational intelligence.
Listado em Official MCP Registry (5)
-
Valid and reliable data engineering and statistical analysis without hallucinations.
-
Research graph MCP for hypotheses, goals, runs, source quality, audits, and generated maps.
-
Search Lacuna's ML research graph for papers, directions, authors, venues, and hypotheses.
-
Verifies AI-written references; finds real papers, evidence, datasets and research tools; PRISMA.
-
ScienceToStartup Buildability Oracle
Signed Buildability Oracle for AI-for-science papers. ed25519 receipts, Wave proofs, divergence.
Listado em PyPI (MCP servers) (5)
-
Search Lacuna's ML research graph for papers, directions, authors, venues, and hypotheses.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Find & fetch research datasets across 21 archives, omics registries, and literature sources.
-
endnote-mcp io.github.gokmengokhan/endnote-mcp
Search, cite, and read PDFs from your EndNote library in Claude Desktop
-
MCP server for the Semantic Scholar API: search 200M+ papers, citations, authors, recommendations.
Listado em npm registry (MCP servers) (5)
-
Real-time web search, reasoning, and research through Perplexity's API
-
AI visibility and SEO data for AI agents: citations, keywords, trends, and scheduled trackers.
-
google-surf-mcp io.github.HarimxChoi/google-surf-mcp
Web, academic and code search with graph RAG, data lineage, ontology and cross-project schema links.
-
140 deterministic tools for your AI: logs, tests, SQL, diagrams, SPARQL. Local, no network.
-
Catch AI-fabricated citations (real DOI + fake title). Retraction, open-access, 10,000+ CSL styles.
Encontrados pelo significado, não por código ou repositório em comum: plugins semelhantes continuam sendo produtos distintos, e isto não é uma avaliação nem uma recomendação.
Quer esta marca no seu plugin em nosso catálogo?
Prove que o mantém com um arquivo no repositório, um arquivo no seu domínio ou um registro DNS, e você poderá mostrar esta marca na ficha, com banners ao vivo para o seu site e o README. Como funciona a verificação
Você também recebe alertas quando um marketplace o publica, o remove, muda a marca de verificado ou o que ele pede, e o endpoint remoto passa a ser monitorado como um serviço web.
Dados de Community GitHub marketplaces. Os números vêm das nossas próprias passagens regulares pelos marketplaces, última leitura em . Não publicamos dados de contato dos editores de plugins.