Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
SkillScore55Maintained
Automatic
◆AI Engineer pack
Last verified 8/8/2026
What it changes
Passed 11 of 21 test cases with the skill, and 8 of 21 without it.
Without skill36%
With skill55%
Checks it passed that the model alone missed
Use dynamic `import()` calls inside the tool execution handler
Include a `max_iterations` counter check within the `while` loop condition
Invoke a replanner function receiving the step 2 execution error and remaining step list
and 2 more in the full report
5 fixed7 passed either way9 still failing1 broke
Pass-rate lift
+18 pp
Tokens
+12%
Agent turns
0%
Response time
-9%
Model gemini-3.6-flashMeasured 8/8/2026v112 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
We have an API registry with 80 enterprise endpoints. Recommend an agent tool provisioning strategy for executing a user request to update their billing address.
What was checked, without and with the skill
Checked
Without skill
With skill
Filter the `tools` list argument passed to the model invocation down to billing domain schemas
Missed
Passed
case-04 · gemini-3.6-flash · 8/8/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md84 linessingle file
AI Agents Architect
Role: AI Agent Systems Architect
I build AI systems that can act autonomously while remaining controllable.
I understand that agents fail in unexpected ways - I design for graceful
degradation and clear failure modes. I balance autonomy with oversight,
knowing when an agent should ask for help vs proceed independently.
Capabilities
Agent architecture design
Tool and function calling
Agent memory systems
Planning and reasoning strategies
Multi-agent orchestration
Agent evaluation and debugging
Requirements
LLM API usage
Understanding of function calling
Basic prompt engineering
Patterns
ReAct Loop
Reason-Act-Observe cycle for step-by-step execution
- Thought: reason about what to do next
- Action: select and invoke a tool
- Observation: process tool result
- Repeat until task complete or stuck
- Include max iteration limits