253 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 253 plugins that match these filters.
linkedin-skillssergebulaev/linkedin-skills1
baoyu-skillsJimLiu/baoyu-skills1
pm-skillsphuryn/pm-skills1
pm-claude-skillsmohitagw15856/pm-claude-skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplace47 marketing skills across 8 pods: Content, SEO & AEO, CRO, Channels, Growth, Intelligence, Sales enablement, and X/Twitter growth. 62 Python tools, 89 reference docs.
14 bundled product skills with 19 Python tools: product-skills fork-orchestrator with continuous-discovery loop (deterministic 16-lane router, Torres cadence tracker, OST linter, /cs-product + /cs-grill-product + /cs-product-loop), product manager toolkit (RICE, PRDs), product strategist, UX researcher, UI design system, competitive teardown, landing page generator, SaaS scaffolder, product analytics, experiment designer, product discovery, roadmap communicator, spec-to-repo, design-qa (UI finish gate: inert controls, missing states, rendered WCAG 2.2 checks). Companion standalone plugins: agile-product-owner, code-to-prd, apple-hig-expert, research-summarizer, design-qa.
9 project management skills with 15 Python tools: pm-skills fork-orchestrator with agentic delivery loop (deterministic 8-lane router, Jira MCP snapshot bridge to Kanban flow metrics + Monte Carlo forecasts, delegation-governance gate, /cs-pm + /cs-grill-pm + /cs-pm-loop), senior PM, scrum master, Jira expert, Confluence expert, Atlassian admin, template creator, meeting analyzer, team communications. Bundled Atlassian Remote MCP.
Organic LinkedIn presence, end to end, with LinkedIn's own rules enforced in code. Orchestrator (context: fork) gates every request against User Agreement §8.2 — refusing automation, scraping, engagement pods, bulk DMs, fake identity and fabricated proof, each with a compliant substitute — then routes to profile / strategy / content / engagement / analytics. Headline and whole-profile scoring with fixes ranked by points per hour; positioning brief with a mandatory exclusion list; cadence priced against real hours with a 90-minute floor; newsletter eligibility + six-month sustainability gate; post linter blocking on engagement bait and screen-reader-hostile Unicode pseudo-bold; repurposing with a reuse ledger; capped commenting roster and template-refusing outreach; analytics that test patterns against a seeded permutation null and refuse to conclude below 10 posts. 17 stdlib tools, 15 references with per-claim confidence levels. No credentials, no API calls, nothing auto-sent. Answers
Internal BizOps domain. v2.8.0 ships 7 skills: orchestrator + process-mapper (BPMN/bottleneck/cycle-time, Lean+TOC) + vendor-management (scorecard+SLA+3rd-party risk, NIST SP 800-161/ISO 27036) + capacity-planner (Erlang-C queueing math for ops teams, NOT engineering) + internal-comms (ADKAR+Kotter 8-step, NOT marketing) + knowledge-ops (SOP+runbook+KB hygiene with 5W2H, context: fork) + procurement-optimizer (UNSPSC spend categorization + supplier consolidation). Orchestrator uses context: fork to route inquiries via Matt Pocock grill discipline (one question per turn, recommended answer, canon-cited challenge). Every SKILL.md ships a Forcing-question library section. 18 stdlib Python tools, 24+ reference docs. Distinct from business-growth (external sales) and c-level-advisor (strategic).
Per-deal-and-packaging Commercial domain. v2.8.0 ships 8 skills: orchestrator + pricing-strategist (model picker + Van Westendorp WTP + packaging) + deal-desk (deal scorer + discount approval routing + redline) + partnerships-architect (5-tier classifier + joint GTM + revshare modeler) + channel-economics (cost-to-serve + ROI + mix optimizer) + commercial-policy (data-backed discount matrix + exception flow + linter) + rfp-responder (Shipley structured RFP/RFI/RFQ + win-theme + winrate predictor, context: fork) + commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Hard rules: pricing outputs model+range (never a single number), deal outputs route to named human approver (never auto-approve), forecast outputs surface conversion assumption, RFP never invents claims for GAP requirements. 21 stdlib Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic), fi
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.
Convert long markdown files into world-class single-file interactive HTML — DOMAIN COMPLETE at v2.10.3 (5 skills). v2.10.3 adds md-slides, the slide-deck converter (arrow/Space/PgDn/Home/End/P navigation, presenter mode with clock + speaker notes + next-slide preview, URL-hash deep linking, @media print page-per-slide for browser-native PDF export; vanilla JS only; Prism.js opt-in via --syntax). Joins md-review (v2.10.2 code-review converter: 2-col diff, severity-tagged margin annotations, WCAG-1.4.1 badges, named reviewer footer), md-document (v2.10.1 long-form: sticky TOC, scrollspy, search, code-copy, Prism autoloader), markdown-html-orchestrator (v2.10.0 context: fork; deterministic doc-type classifier), and design-system (v2.10.0 onboarding wizard; WCAG-AA 12-token palette). 15 stdlib-only Python tools, 15 references, 4 template assets. Inspired by Thariq Shihipar's Claude Code HTML output essay.
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.
Bundle of 12 LinkedIn marketing skills for Claude Code and Codex with verified 2026 hook formulas, comment + reply templates that earn author replies, a unified humanizer (rewrite + `--mode audit` pre-publish check, plus bundled emoji-detector, detector-spread tester, rule-explainer sub-tools), profile rewriter, content planner, employee advocacy playbook, thread monitor (warm-reply window author-reply tracking), and engager analytics (likers + commenters ICP segmentation), interviewer (Story Bank of receipts, turning points and positions).
productivityContent generation, AI backends, and utility tools for daily work efficiency
PM utility skills: resume review, NDA drafting, privacy policy generation, and grammar/flow checking. Essential tools for product managers beyond core product work.
4 finance skills: financial analyst (ratio analysis, DCF valuation, budgeting, forecasting), SaaS metrics coach (ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio, projections), business investment advisor, and month-end close (close calendar, reconciliation proof, flux gate). 10 Python automation tools.
12 Claude Cowork-native skills that act on your real data through connectors and the sandbox — Gmail/Calendar inbox triage, meeting prep and follow-up sweeps; Drive/Docs/Sheets audits, restructures and decks; Notion/Slack decision logs, DB hygiene and async standups; GitHub/Linear issue triage, PR descriptions and changelogs. Each drives real tools and returns an artifact — not a framework you run by hand.
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.
DCC software. A lead and fourteen specialists that drive Blender 5.2 through Python, headless or in a live session: sculpting, retopology, UVs and baking, shading, hair, rigging, animation, previs, blockouts for render-to-real video, Geometry Nodes, lighting, Grease Pencil, hard surface, export to game engines. Twelve test suites pass headless on Blender 5.2.1.
DCC software. A lead and ten specialists that drive Autodesk Maya 2027 through Python, batch or live: modeling, retopology and UVs, rigging, skinning, animation, groom, FX, look dev, Arnold lighting and rendering, pipeline scripting.
Game engine. A lead and nine specialists that drive Unreal Engine 5.8 on macOS through Editor Python, headless jobs, and Epic's Unreal MCP server: world building, materials, lighting and rendering, gameplay, animation, cinematics, VFX, pipeline automation, performance.
Game engine. A lead and thirteen specialists that drive Unity 6.3 LTS on macOS through batch mode, a live editor, and command-line builds: architecture, gameplay, 2D, animation, UI, VFX, shaders, rendering and lighting, world building, performance, mobile, Web, pipeline automation. Every procedure was run live in Unity 6.3.
Game engine. A lead and thirteen specialists that drive Godot 4.7 on macOS through headless jobs, windowed captures, GUT and gdUnit4 tests, and command-line exports: architecture, gameplay, 2D, 3D worlds, animation, UI, VFX, shaders, rendering and lighting, audio, multiplayer, performance and export, pipeline automation. Every procedure was run live in Godot 4.7.2.
