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Design, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent architecture through orchestration, memory systems, safety guardrails, and operational excellence.
Passed 15 of 22 test cases with the skill, and 2 of 22 without it.
13 fixed2 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
The instructions your model reads when the skill loads.
Build agents that actually work in production. Not demos. Not toys. Real systems that run 24/7, handle edge cases, and compound value over time.
This skill covers the entire agent lifecycle: architecture → build → deploy → operate → scale.
Before writing a single line of config, answer these:
agent_brief:
name: "" # Short, memorable (max 2 words)
mission: "" # One sentence — what does this agent DO?
success_metric: "" # How do you MEASURE if it's working?
failure_mode: "" # What does failure look like?
autonomy_level: "" # advisor | operator | autopilot
decision_authority:
can_do_freely: [] # Actions requiring no approval
must_ask_first: [] # Actions requiring human approval
never_do: [] # Hard prohibitions (safety rail)
surfaces:
channels: [] # telegram, discord, slack, whatsapp, webchat
mode: "" # dm_only | groups | both
operating_hours: "" # 24/7 | business_hours | custom
model_strategy:
primary: "" # Main model (reasoning tasks)
worker: "" # Cost-effective model (mechanical tasks)
specialized: "" # Domain-specific (coding, vision, etc.)
Choose deliberately. Most failures come from wrong autonomy level.
| Level | Description | Best For | Risk |
test cases passed, vs 2 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.