131 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 131 plugins that match these filters.
starkf0d010c/stark1
psenger-skills-marketplacepsenger/ai-agent-skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplacePlan features as PRPs (Product Requirements Prompts): implementation blueprints with requirements, codebase context and validation steps, then execute them
A cross-vendor, review-gated implementation loop: dispatch coding units to Codex (pinned plain codex exec) or a sandboxed Claude Code (claude -p in a git-less copy), have the other vendor's model review the diff, iterate, gate on the full test suite, then ship as a PR. Encodes hard-won environment constraints (read-only git, no full-suite runs, stuck-job handling) and eight user-configurable dials.
Goal-first engineering ownership — investigate, root-cause, design, plan, then delegate implementation unit-by-unit to implementation-loop, with honest artifact-level verification. Requires the implementation-loop plugin plus an authenticated backend CLI.
Research-backed Hinge profile optimization covering audit, discovery, photo strategy, prompt writing, settings, implementation, and post-launch review.
Multi-platform UI/UX design plugin for AI coding agents. Routes product flow, platform idiom, originality, motion, assets, and tokens before implementation.
Explores a codebase for architectural friction through the lens of Ousterhout's deep-module principle (small interface, large implementation). Seven-step interactive workflow: an Explore sub-agent navigates the codebase organically — the friction it experiences IS the signal. Surfaces candidate clusters with coupling reasons, call patterns, shared types, dependency categories, and existing tests that a boundary test would replace. User picks what to explore, frames the problem, then 3–4 parallel sub-agents design competing deep-module interfaces. Chosen design becomes a structured RFC action file readable by GitHub MCP or ROVO (Jira) MCP. Use when the user says "arch review", "find shallow modules", "module depth", "deep module", "Ousterhout", "testability audit", "surface coupling", "design interfaces", "RFC issues", or "architectural friction".
Trace BIRD implementation behavior through exact source revisions and runtime paths.
development
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.
When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.
Transform project descriptions and feature requests into comprehensive specifications and actionable task lists. Use when the user wants to: (1) Create a specification from a project/feature description, (2) Generate a detailed plan with task breakdown, (3) Clarify requirements before implementation, (4) Convert ideas into structured development plans with progress tracking. Works with or without existing codebase files.
