turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.
- ✓Open-source license (Apache-2.0)
- ✓Recently active
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
git clone https://github.com/evo-hq/evo && cp evo/*.md ~/.claude/agents/7 items en este repositorio
Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project.
Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance.
Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests.
Protocol that evo optimization subagents follow when dispatched from /optimize. Auto-loaded by spawned subagents via their host's skill loader. The orchestrator may also invoke this skill to understand the brief shape its dispatched subagents expect + what they're required to emit -- useful when writing briefs or debugging a subagent's behavior.
This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/.
Land the winning experiment from an evo run as a clean, mergeable change -- open a PR when the repo has a remote, otherwise merge into the working branch. Distills the best-scoring experiment down to the minimal diff that reproduces its behaviour, shaped for the qualities a maintainer merges on (scope discipline, test integrity, style adherence), then attaches an advisory mergeability report. Use when the user invokes /evo:ship, asks to land/merge/ship the best result, or wants to turn a finished optimization into a pull request.
Resumen de Subagents
Lo que la gente pregunta sobre evo
¿Qué es evo-hq/evo?
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evo-hq/evo es subagents para el ecosistema de Claude AI. turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents. Tiene 1.5k estrellas en GitHub y su última actualización registrada es del 2026-07-17.
¿Cómo se instala evo?
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Puedes instalar evo clonando el repositorio (https://github.com/evo-hq/evo) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar evo-hq/evo?
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Nuestro agente de seguridad ha analizado evo-hq/evo y le ha asignado un Trust Score de 92/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene evo-hq/evo?
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evo-hq/evo es mantenido por evo-hq. La última actividad registrada en GitHub es del 2026-07-17, con 37 issues abiertos.
¿Hay alternativas a evo?
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Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.
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