00-andruia-consultant
Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
Autonomous agents are AI systems that can independently decompose
$ npx -y skills add sickn33/antigravity-awesome-skills --skill autonomous-agents --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/autonomous-agentsContext preview
The summary Claude sees to decide when to auto-load this skill.
Autonomous agents are AI systems that can independently decompose
name: autonomous-agents description: Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. risk: critical source: vibeship-spawner-skills (Apache 2.0) date_added: 2026-02-27
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% by step 10. Build for reliability first, autonomy second.
2025 lesson: The winners are constrained, domain-specific agents with clear boundaries, not "autonomous everything." Treat AI outputs as proposals, not truth.
Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
class ContextManager: def __init__(self, max_tokens=100000): self.max_tokens = max_tokens self.messages = []
def add(self, message): self.messages.append(message) self.maybe_compact()
def maybe_compact(self): if self.token_count() > self.max_tokens * 0.8: self.compact()
def compact(self):
system = self.messages[0]
recent = self.messages[-10:]
middle = self.messages[1:-10] if middle: summary = summarize_messages(middle) self.messages = [system, summary] + recent
**User request:**
> Use @autonomous-agents for this task: Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance.
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Repo: sickn33/antigravity-awesome-skills
Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
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