Individual skill
subagent
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.
plugins/evo/skills/subagent/SKILL.md
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- Not checked yet
- Last checked
- Nov 3, 2026
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Repository context
- Repository stars (not skill ratings)
- 1,497
- Repository last updated
- Oct 5, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- autonomous-agents Repository topic
- autoresearch Repository topic
- claude-code Repository topic
- code-optimization Repository topic
- codex Repository topic
- evolutionary-algorithms Repository topic
- llm-agents Repository topic
- writing Derived category
- testing Derived category
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Read excerpt
# Evo Subagent Protocol
**Orchestrators reading for context**: this is the protocol your dispatched subagents follow. You don't act on it yourself -- write briefs that satisfy the four required fields described below, and rely on each spawned subagent to drive the loop on its end. Stop reading at "Host conventions" if you only need the brief shape; the rest is for the subagent.
## Evo surface -- subagent perspective
What you can pull/dispatch/read as a subagent. Each line is a triggering condition.
```
skills you may pull (Skill tool)
└── evo:finetuning before writing or changing any train.py -- technique
choice, training recipe, observability, retry discipline.
subagents you dispatch (Task tool, subagent_type=...)