evo
Structured experiment-driven code optimization using tree search and parallel subagents
Paquete de plugins · de evo-hq
Resumen
evo es un paquete de plugins para herramientas de programación con IA publicado por evo-hq. Marketplaces que leemos y que lo publican: 1 (Community GitHub marketplaces). El último cambio que registramos fue el 2026-10-21. Según nuestra pasada por los marketplaces del 2026-10-22.
Qué pide
- Se instala como paquete de plugins
- Hooks declarados: 7
Lo que declara, pide y ejecuta, completo
Instala solo plugins de desarrolladores en los que confíes. Mostramos lo que publican los marketplaces y no probamos plugins.
Funciona con
- Claude Code
Según los marketplaces que lo listan y el transporte MCP que declara, tal como lo documenta cada cliente. No probamos plugins.
Conectar
Comandos y configuraciones generados solo a partir de lo que declaran sus marketplaces. No los ejecutamos por ti ni probamos plugins.
Como plugin de Claude Code
Generado a partir de lo que declara Community GitHub marketplaces.
/plugin marketplace add evo-hq/evo
/plugin install evo@evo-hq-evoDónde está publicado
| Marketplace | Estado | Versión | Cifras | Verificado | Visto por primera vez |
|---|---|---|---|---|---|
| Marketplace de la comunidad evo-hq/evo (Abrir el código en GitHub) | Publicado | 0.8.0 | Forks (GitHub): 115 Estrellas (GitHub): 1 479 |
Sin marca |
Cada cifra es del propio marketplace y nunca se suma entre marketplaces. Un marketplace que no publica cifras no muestra ninguna: sin número no es cero.
Figura en un marketplace de la comunidad
| Marketplace | Repositorio | Estrellas (GitHub) |
|---|---|---|
| evo-hq-evo | evo-hq/evo | 1 479 |
Cómo han cambiado sus cifras
- 2026-10-191,5 mil
- 2026-10-201,5 mil
- 2026-10-211,5 mil
Cada punto es un día en que leímos un número distinto; los tramos planos son días en que el número no cambió. Las cifras de distintos marketplaces nunca se suman.
Qué contiene el paquete
Tal como se publica en Community GitHub marketplaces.
Skills: 7
discoverfinetuninginfra-setupoptimizereportshipsubagent
Comandos: 2
discoveroptimize
Agentes: 3
benchmark-reviewerideatorverifier
Hooks: 6
PostToolUsePreToolUseSessionStartStopSubagentStopUserPromptSubmit
Qué cambió
- Pasó a ser un producto que seguimos
- Community GitHub marketplaces: apareció
Plugins similares
Productos cuyos propios nombres, descripciones, herramientas y skills son los más cercanos a este por su significado, en todos los marketplaces que leemos. La cercanía se ordena solo dentro de esta lista.
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
-
Autonomous LLM agent optimization using LangSmith. Spawns 5 parallel proposers in git worktrees, evaluates candidates via LangSmith experiments, and merges winners automatically…
-
Research harness for optimizing code with the GEPA algorithm (LLM-driven genetic-Pareto search).
-
Autonomous experiment loop — optimize any file by a measurable metric. 5 slash commands (/ar:setup, /ar:ar-run, /ar:loop, /ar:ar-status, /ar:ar-resume), 8 built-in evaluators…
-
Profiling-driven code optimization workflow. Builds Regression Test and Benchmark Test infrastructure first, then runs an autonomous optimization loop to iteratively improve…
-
The context exoskeleton for AI development: optimize the entire development lifecycle to reduce token usage and context occupancy.
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered…
-
Official Codex Desktop plugin for Evolver: GEP workflows, local Proxy MCP tools, and auditable agent self-evolution.
Plugins similares por marketplace
La misma pregunta a cada marketplace por separado: ¿hay allí un equivalente de este plugin?
Publicado en Claude Code: claude-plugins-community (5)
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
-
Autonomous LLM agent optimization using LangSmith. Spawns 5 parallel proposers in git worktrees, evaluates candidates via LangSmith experiments, and merges winners automatically…
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered…
-
Run Codeflash as a background agent in Claude Code to automatically optimize Python, Java, JavaScript, and TypeScript code for performance. Codeflash analyzes your code…
Publicado en Claude Code: claude-plugins-official (5)
-
Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered…
-
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
-
Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and…
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Output.ai workflow development toolkit for Claude Code. Adds 5 specialist agents (planner, builder, debugger, prompt writer, quality reviewer), 40+ slash-command skills covering…
Publicado en Claude: knowledge-work-plugins (5)
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Keep your coding agent up to date with the latest web best practices
-
MCP server for terminal commands, file operations, and process management
Publicado en Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
AI-powered code review in Codex, powered by CodeRabbit.
-
Cloudflare platform plugin with curated skills for Workers, Wrangler, and Agents SDK plus the official Cloudflare API MCP server.
Publicado en Community GitHub marketplaces (4)
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
-
Research harness for optimizing code with the GEPA algorithm (LLM-driven genetic-Pareto search).
-
Autonomous experiment loop — optimize any file by a measurable metric. 5 slash commands (/ar:setup, /ar:ar-run, /ar:loop, /ar:ar-status, /ar:ar-resume), 8 built-in evaluators…
-
Profiling-driven code optimization workflow. Builds Regression Test and Benchmark Test infrastructure first, then runs an autonomous optimization loop to iteratively improve…
Publicado en Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Model, visualize, and deploy applications with Radius from the GitHub Copilot app and CLI.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Meta prompts that help you discover and generate curated GitHub Copilot agents, instructions, prompts, and skills.
-
7 specialized agents covering the full software development lifecycle from UX design and architecture to security and DevOps.
Publicado en Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
-
Advanced Security plugin for GitHub Copilot.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
code-apps-preview
Build and deploy Power Apps code apps using React, Vite, and Power Platform connectors.
Publicado en Cursor: cursor/plugins (5)
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
if you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence.
-
Skills for building on the Cursor Origin API. Fetch the live spec first, then follow the Origin rules for credentials, scopes, webhooks, paging, and errors. Includes a skill that…
-
Build apps, scripts, and automations with the TypeScript SDK.
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
Publicado en Docker MCP Catalog (5)
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Giving Claude ability to run code with E2B via MCP (Model Context Protocol).
-
Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.
-
Tools and resources for writing Effect code in Typescript.
Publicado en Official MCP Registry (5)
-
Optimization middleware for AI agents: JSON problem in, verified and ranked solutions out.
-
ai-prompt-optimizer io.github.lazymac2x/ai-prompt-optimizer
Cloudflare Workers MCP server: ai-prompt-optimizer
-
Multi-model AI orchestration MCP server with code review, compare, and debate tools.
-
orbit io.github.constellation-works/orbit
Orbit's local-first task and workflow registry for coding agents.
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
Publicado en npm registry (MCP servers) (5)
-
One workspace for every AI coding assistant. Shared tasks, memory, and governance.
-
depwire io.github.atef-ataya/depwire
Dependency graph + 24 MCP tools. Impact analysis, simulation, security, agent coordination
-
Browser-local and CLI static evidence for deployed AI model artifacts.
-
mcp com.dechonet/mcp
30 security tools for AI agents: phishing links, exposure maps, DNS, SSL, PQC, history, pivots.
-
dealflowpro io.github.jbechtel-97/dealflowpro
Multifamily real estate deal analysis — cap rate, DSCR, IRR, DFP Score, max offer price
Encontrados por significado, no por código ni repositorio compartidos: los plugins similares siguen siendo productos distintos, y esto no es una reseña ni una recomendación.
Comparada lado a lado
¿Quieres esta marca para tu plugin en nuestro catálogo?
Demuestra que lo mantienes con un archivo en su repositorio, un archivo en tu dominio o un registro DNS, y podrás mostrar esta marca en la ficha, con banners en vivo para tu web y tu README. Cómo funciona la verificación
Además recibirás avisos cuando un marketplace lo publique, lo retire, cambie su marca verificada o lo que pide, y su endpoint remoto quedará monitorizado como un servicio web.
Datos de Community GitHub marketplaces. Las cifras proceden de nuestros propios recorridos periódicos por los marketplaces, leída por última vez el . No publicamos datos de contacto de los editores de plugins.