23 plugins de marketplaces públicos do Claude Code. Cada um agrupa skills, slash commands, agents, hooks ou MCP servers que são instalados juntos.
Mostrando 23 plugins que correspondem a estes filtros.
claude-code-workflowswshobson/agents2
agent-powerupsyeaight7/agent-powerups2
brooks-lint-marketplacehyhmrright/brooks-lint1
pm-skillsphuryn/pm-skills1Envie o repo com .claude-plugin/marketplace.json e nós listaremos cada plugin.
Enviar marketplaceInternal 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).
Build, launch, grade, and schedule Claude Managed Agents (CMA) in your own Anthropic account — a plugin re-implementation of Anthropic's launch-your-agent reference skill (Apache-2.0; independent, not a fork). Every session starts with a goal (./my-agent/goal.json, opt-in SessionStart hook, driven by /cs-goal); loop_compiler.py compiles it into a bounded grade->iterate loop (max_iterations 1..20), a recurring cron scheduled-deployment loop, or a single-pass interview->stage->launch workflow. 6 skills: orchestrator (context: fork goal router) + interview + stage-launch + grade-iterate + run-without-you + wrap-up. 18 stdlib-only deterministic scaffolders (no network/API calls; live launches emitted as BYOK curl that never prints the key), 4 agents, 8 commands, hooks, 5 references, 4 assets. Validators enforce CMA limits. Distinct from engineering/agent-harness (generic domain loop) and write-a-skill (authors Claude Code skills, not CMAs).
ETL pipeline construction, data warehouse design, batch processing workflows, and data-driven feature development
AI code reviews grounded in twelve classic engineering books — decay risk diagnostics with book citations, severity labels, and six analysis modes (PR review, architecture audit, tech debt, test quality, health dashboard, full-sweep auto-fix)
AI image generation with creative workflow orchestration, prompt engineering, and curated inspiration library via MCP server
Moved to phuryn/product-engineering, which maintains the AI Shipping Kit in its ai-shipping plugin; the skills and commands here only say where each one went.
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.
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.
Knowledge base compiled from OpenAI's Spinning Up in Deep RL (MIT, Joshua Achiam) by engineering/book-to-skill. A resident core carries the RL optimization problem, the model-free taxonomy, the policy-gradient template with its five valid weights, the safe-step family (VPG to TRPO to PPO) and the overestimation family (DDPG to TD3 and SAC); 20 on-demand chapters cover key concepts and MDPs, the algorithm taxonomy and model bias, the policy gradient derivation with the log-derivative trick and EGLP lemma, Achiam's researcher essay, the key-papers topic map, the exercises including the silent DDPG broadcasting bug, the benchmark parity disclosure, one chapter per algorithm, and the logger/MPI/ExperimentGrid utilities. Ships a glossary, a patterns file with 16 techniques, a decision cheatsheet with thresholds, a cs-spinning-up-deep-rl agent and /cs-spinning-up-deep-rl. Structured study notes, not a reproduction of the source.
Design engineering skill + system for AI coding agents: anti-slop UI rules, outcome recipes, spec-driven design (/sddesign), design-review + a11y agents, and MCP quality gates.
AI-powered development tools that get smarter with every use. Make each unit of engineering work easier than the last. Includes 18 specialized agents, 19 commands, 29 skills, and 4 hooks, 1 MCP server.
Spec-driven development and context engineering for AI coding agents, backed by project context in Git.
Risk-graded context-engineering skills, command prompts, and change-record templates. No hooks are configured, so nothing runs automatically; the bundled ng CLI is included for repo-side use (run from a checkout) and runs nothing on its own.
Modernize COBOL, DB2, VSAM, and JCL systems with evidence-first archaeology, REQ-NNN lineage, bounded correction loops, an extracted engineering graph, behavior and data equivalence proof, and human-gated delivery.
Modernize COBOL, DB2, VSAM, and JCL systems with the four-stage classic workshop: evidence-first archaeology, REQ-NNN lineage, bounded implementation, and hardened evolution, without the correction-loop and engineering-graph layer.
Modernize Software AG Natural and Adabas systems with evidence-first archaeology, REQ-NNN lineage, bounded correction loops, an extracted engineering graph, behavior and data equivalence proof, and a preview-first workspace publisher.
Modernize Software AG Natural and Adabas systems with the four-stage SIFAP workshop: evidence-first archaeology, REQ-NNN lineage, bounded implementation, and hardened evolution, without the correction-loop and engineering-graph layer.
Analytics engineering, dbt patterns, BigQuery optimization, data quality, and pipeline workflows.
developer toolsSubagent orchestration, wave execution, persistent completion, autonomous delivery, and migration batching.
developer tools
Feature creation, selection, and transformation tools
