61 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 61 plugins that match these filters.
ai-marketing-hub-claude-adsAgriciDaniel/claude-ads1
claude-code-plugins-plusjeremylongshore/tons-of-skills-marketplace1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceFounder-mode executive team plugin: 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, Chief of Staff, General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, VP of Engineering) with distinct cognitive voices, plus 21 /c-level-agents:* slash commands — forcing-question office hours (CFO/CMO/CPO/CRO/CTO/CISO/GC/CDO/CAIO/CCO/VPE reviews), strategic sprint pipeline (brief → boardroom → decide → execute → post-mortem), and meta routing (/c-level-agents:founder-mode auto-router, /cs-onboard, /c-level-agents:cross-eval multi-model consensus, /c-level-agents:freeze cooldown lock). Wraps the 33 c-level skills with cognitive gearing, persona voice, and artifact-driven handoffs. The business-domain answer to YC Garry Tan's gstack.
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 (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.
Compliance OS — meta-orchestrator for multi-framework compliance programs spanning 9 frameworks (ISO 27001, ISO 13485, ISO 42001, ISO 14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR). Framework selector, cross-framework control mapper, audit simulator, and consolidated evidence-pool generator (stdlib Python), plus 3 cs-* compliance agents and 3 /cs-* readiness commands.
A second brain for Claude Code + Obsidian inspired by Karpathy's LLM Wiki gist. Turn any LLM CLI into a disciplined wiki maintainer: incrementally ingest sources into a persistent, interlinked markdown vault; update entity/concept/source pages; flag contradictions; maintain index and append-only log. Knowledge compounds instead of being re-derived by RAG on every query. Ships 3 sub-agents (wiki-ingestor, wiki-librarian, wiki-linter), 5 slash commands (/wiki-init, /wiki-ingest, /wiki-query, /wiki-lint, /wiki-log), 8 Python tools (stdlib only: init_vault, ingest_source, update_index, append_log, wiki_search BM25, lint_wiki, graph_analyzer, export_marp), 8 reference docs, full vault templates (CLAUDE.md, AGENTS.md, cursorrules, 5 page templates), and a worked example vault. Cross-tool compatible with Claude Code, Codex CLI, Cursor, Antigravity, OpenCode, and Gemini CLI.
Claude-first, portable paid-media operations across 12 advertising platforms with source-grounded audits, deterministic findings and evidence coverage, lifecycle workflows, versioned JSON reports, and capability-gated account changes.
Frontend UI development and mobile application implementation across platforms
Cross-platform application development coordinating web, iOS, Android, and desktop implementations
Comprehensive codebase cleanup across 11 quality dimensions — dead code, duplication, weak types, circular deps, defensive cruft, legacy code, AI slop, type consolidation, security, performance, and async patterns. Confidence scoring and build verification gates.
Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.
Database migration automation, observability, and cross-database migration strategies
Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator covering frontmatter/safety/budget/index, pre- and post-flight token budget estimator with a worth-converting verdict, and a plugin emitter that wraps a compiled skill as an installable claude-skills package behind a rights gate), 5 references citing 7-8 sources each, a cs-book-to-skill agent, and /cs-book-to-skill + /cs-book-to-plugin commands. Derived from virgiliojr94/book-to-skill (MIT).
Engineer an agent's forgetting, not just its remembering. Four deterministic stdlib scripts implement the four lenses of agent memory: a cost profiler that splits construction from query spend and reports cost per correct answer (construction energy exceeds total query energy across 300 queries in the Stanford characterization); an architecture picker that scores the four paradigm families — long-context, flat RAG, structure-augmented RAG, agentic — disqualifies on hard constraints, names the cost the winning choice makes you pay, and refuses to pick when the top two tie; a density auditor that classifies every record in a memory directory or JSONL export as FACT / SKILL / LOG / PROSE, finds near-duplicates, and flags stale wording; and a forgetting-policy linter that fails any design with no forgetting rule. Ships cs-memory-engineer agent, /cs-memory-engineering and /cs-forgetting-audit commands, 4 references, and a seven-question forcing worksheet.
Get medical device software through IEC 62304 and IEC 81001-5-1. Four deterministic stdlib scripts: a software safety classifier (62304 4.3 with A1 external controls and segregation) that also sets the FDA Basic/Enhanced documentation level and flags 524B cyber devices; a lifecycle gap check scoped by class, with IEC 81001-5-1 security activities; a SOUP register check with SBOM cross-check; and a trace matrix release gate. Ships cs-device-software-lead agent, /cs-medical-device-software and /cs-soup-review commands and 4 references with per-claim confidence levels.
Distributed system tracing and debugging across microservices
Relentless plan-and-design interrogator. Walks the decision tree one branch at a time, asking forcing questions sequentially with recommended answers. Explores codebase before asking. Derived from Matt Pocock's MIT-licensed grill-me with: (1) 3 stdlib Python tools (decision-tree extractor across 6 branch kinds, question generator with dependency-aware ordering, JSON-backed session tracker for multi-day grills), (2) 3 references citing 7-8 sources (6 forcing-question patterns, when to stop grilling, companion tooling), (3) cs-grill-master persona agent + /cs-grill-me slash command. Matt's relentless one-at-a-time interview discipline preserved verbatim per MIT.
Conversation-handoff document generator. Compacts the current session into a markdown handoff for a fresh agent — references existing artifacts (PRDs, plans, ADRs, issues, commits) by path/URL instead of duplicating them. Derived from Matt Pocock's MIT-licensed handoff with: (1) 3 stdlib Python tools (template generator tailored to 5 next-session emphases, artifact deduplicator across 5 categories of duplication, skill recommender matching content to 14 skills in this repo), (2) 4 references citing 7-8 sources (handoff structure, deduplication discipline, next-session skill matching, companion tooling), (3) cs-handoff-author persona agent + /cs-handoff slash command. Matt's no-duplication discipline + mktemp convention preserved verbatim per MIT.
Decision-grade entity research. Due-diligence/background-check/competitor-prep with tier-weighted verdict + citation tracker. Research-pack convention. Path-B from megaprompt 02.
Research orchestrator (hybrid router + fallback). Deterministic SIGNALS classification routes to 6 specialists (pulse/litreview/grants/dossier/patent/syllabus) at >=2 signals, else runs own 8-step plan-decompose-search-synthesize-cite fallback. Routing transparency mandatory. Path-B from megaprompt 13.
Personal Claude power-user coach. Delivers a personalized, ranked cheat-code glossary on first activation, then surfaces at most one tip per turn when it would genuinely improve the next attempt. Ships cheat-codes glossary, coaching-rules decision tree, three stdlib Python tools, cs-claude-coach agent, and /cs-claude-coach command.
Docs-anchored grilling session — interrogates a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), updating those files inline as terminology and decisions crystallise. Derived from Matt Pocock's MIT-licensed grill-with-docs with stdlib validators (CONTEXT.md linter, ADR scanner, glossary-code consistency), reference docs, cs-grill-with-docs agent, and /cs-grill-with-docs command.
