16 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 16 plugins that match these filters.
pstack-claudemichael-denyer/pstack-claude1
wondelai-skillswondelai/skills1
mastermindmehrad-dm/mastermind1
agent-skillsSteveVitali/agent-skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceIf you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence. Original pstack by Lauren Tan (poteto).
Twelve-skill bundle covering the 《经济学(季刊)》 manuscript lifecycle: workflow router, fit positioning, internationally-legible topic selection, field-benchmarked literature review, structural / quasi-experimental identification, modern staggered-DID compliance, inference rigor, mechanism evidence, figures-over-tables, English abstract, submission preflight, and rebuttal.
academicTwelve-skill bundle covering the Communication Research (CR) manuscript lifecycle — hypothesis-testing experiments, surveys, and content analysis with rigorous measurement, mediation/moderation, and APA reporting.
academicTwelve-skill bundle covering the Journal of Applied Psychology manuscript lifecycle — I-O theory, measurement and design rigor, SEM/HLM/meta-analysis, masked review, and TOP-aligned open science.
academicTwelve-skill bundle covering the 《南开管理评论》 manuscript lifecycle: workflow router, fit positioning, theory-gap articulation, mechanism-backed hypothesis development, measurement rigor (reliability / validity / common-method-bias), survey-SEM (mediation / moderation / moderated mediation / HLM), experiments, multi-case / grounded theory, China contextualization, discussion that advances a management theory, submission preflight, and rebuttal.
academicEleven-skill bundle covering the 《中国社会科学》 manuscript lifecycle: workflow router, fit positioning, problematic framing, original-theory contribution, theory-tradition literature dialogue, argumentation rigor, evidence handling, scholarly style, abstract + keywords, submission preflight, and rebuttal.
academicSystems architecture and distributed systems skills including Designing Data-Intensive Applications (Martin Kleppmann), System Design Interview (Alex Xu), Clean Architecture (Robert C. Martin), Release It! (Michael Nygard), High Performance Browser Networking (Ilya Grigorik), and Team Topologies (Skelton & Pais)
A markdown brain that gives your AI coding tools judgment and rigor. Skills: init, build, debug, performance, qa, interview, learn, signature, persona, route, lint, clarify, deepen, double-check, deprecate, roadmap, assess, constitution, living-docs, specify, blueprint, breakdown, checklist, analyze, converge, prototype, explain, prompt, quarantine, report, handoff, levelup, help + agents: architect, code-reviewer, refactorer, tech-scout. Experimental (v0.33.2).
Rigorous engineering process for AI coding agents: implement-spec, decompose-spec, orchestrate-build, build-memory, synthesize-spec, reconcile-build, self-review, review-pr, address-pr-comments, agent-docs, refresh-repo-docs
AI-native scientific research pipeline. Takes a research goal — optionally with a research paper — and autonomously conducts rigorous, multi-step academic research.
researchRigorous methods for statistics, machine learning, and meta-analysis, from question to paper: pre-specified SAPs, statistical and reporting-checklist review, and reproducible R and Python workflows. Every study compounds.
Research methodology and rigor scaffolds (Iron Laws, rationalization tables, decision flowcharts, systematic-reasoning checklists) (3 skills)
Rigorous multi-pass editor for law review articles, student notes, seminar papers and other legal scholarship. Runs six specialized passes — structure, substantive critique, Bluebook citations, grammar and clarity, fact-checking against sources, and a synthesizing memo — and delivers an editorial memo with issues prioritized as critical, substantial or minor and keyed to specific footnotes and paragraphs. Handles articles of any length, including 50,000-word pieces, by chunking on section boundaries. Reads .docx directly. Use when editing, critiquing, workshopping or pre-submission-reviewing academic legal writing. Triggers on "edit my article," "review this draft," "critique my note," "check my Bluebook citations," "is my argument sound," "read my law review piece," "workshop this paper," "pre-submission review." Chunking needs Python 3; fact-checking needs web search; both degrade gracefully without.
Use for PhD-level expertise in data science, statistics, and machine learning: rigorous statistical analysis, experimental design, causal inference, advanced modeling, research methodology, or data science project leadership. Load when the user asks about statistical methods, experimental design, model selection, A/B testing, hypothesis testing, power analysis, regression, causality, Bayesian analysis, or research methodology. For insurance, actuarial, claims, reserving, solvency, credibility, tail-risk, or financial-risk statistical modeling, use `actuarial-risk-modeling`; for deterministic operating and SaaS financial models, use `financial-modeling`. Do not use this skill for unrelated requests; route to the nearest named specialist.
Plan, conduct, evaluate, and synthesize rigorous research investigations with credible evidence and a traceable method, including source-to-claim closure for media evidence. Do not use this skill for repeated source extraction and durable note orchestration; use `research-and-vault` for that capture workflow, or `ffmpeg` for media operations.
Apply SOLID principles and design patterns to backend code without over-engineering, with a configurable rigor dial.
code-quality
