14 plugins issus de marketplaces Claude Code publiques. Chacun regroupe des skills, des commandes slash, des agents, des hooks ou des MCP servers qui s'installent ensemble.
14 plugins correspondent à ces filtres.
agent-powerupsyeaight7/agent-powerups2
claude-code-skillsalirezarezvani/claude-skills1
evo-hq-evoevo-hq/evo1
investorclawargonautsystems/InvestorClaw1Soumettez le dépôt avec .claude-plugin/marketplace.json et nous listerons chaque plugin.
Soumettre une marketplaceOpen-source investment research terminal integration - comprehensive equity analysis, crypto tracking, macro indicators, portfolio optimization, and AI-powered financial insights using OpenBB Platform
Database query optimization, cloud cost optimization, and scalability improvements
Application profiling, performance optimization, and observability for frontend and backend systems
Interactive debugging, developer experience optimization, and smart debugging workflows
Team workflows, issue management, standup automation, and developer experience optimization
Multi-agent system optimization, agent improvement workflows, and context management
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.
Structured experiment-driven code optimization using tree search and parallel subagents
Analyze DeFi liquidity pools for impermanent loss, APY, and optimization opportunities
Analytics engineering, dbt patterns, BigQuery optimization, data quality, and pipeline workflows.
developer toolsGraph-backed memory and context optimization workflows with graphify first and document conversion helpers second.
developer tools
Get comprehensive performance optimization recommendations
Multi-account portfolio analysis: holdings snapshots, performance metrics, bond analytics (YTM, duration, FRED-backed benchmarks), analyst consensus, news correlation, multi-factor synthesis, optimization, CSV/Excel reporting, and CME futures pricing (Yahoo Finance by default; optional Massive for futures/premium). Deterministic signed-envelope pipeline; built-in financial-advice guardrails (educational output only). Runs the prebuilt ic-engine container over MCP-HTTP. Free by default (Yahoo Finance), no API key required.
financeDeep learning optimization techniques
