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Before diving into tool-calling patterns, structured outputs, and JSON accuracy metrics, you'll build the skill that will guide your learning throughout this chapter. This isn't just preparation—it's the first step in creating a reusable asset you'll refine as you progress.
Passed 21 of 24 test cases with the skill, and 18 of 24 without it.
and 2 more in the full report
3 fixed18 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
When defining performance criteria for a fine-tuned task backend model replacing GPT-4 to run on consumer hardware, what maximum latency target should be specified in the specification?
| Checked | Without skill | With skill |
|---|---|---|
| The spec targets a response latency of less than 500 milliseconds. | Missed | Passed |
The instructions your model reads when the skill loads.
Before diving into tool-calling patterns, structured outputs, and JSON accuracy metrics, you'll build the skill that will guide your learning throughout this chapter. This isn't just preparation—it's the first step in creating a reusable asset you'll refine as you progress.
By the end of this lesson, you'll have a working agentic-tuning skill grounded in official documentation. Each subsequent lesson will test and improve this skill, transforming your learning into accumulated intelligence.
Agentic fine-tuning involves specialized knowledge that's rapidly evolving:
Building a skill from official documentation ensures you're working with current, accurate patterns rather than relying on potentially outdated training data.
Every chapter starts with a clean environment. No assumptions about prior state.
# Navigate to your projects directory
cd ~/projects
# Clone fresh (or pull latest if exists)
git clone https://github.com/panaversity/skills-lab.git ch66-agentic-tuning
cd ch66-agentic-tuning
# Verify structure
ls -la
Output:
drwxr-xr-x skills/
drwxr-xr-x specs/
drwxr-xr-x data/
-rw-r--r-- README.md
-rw-r--r-- requirements.txt
test cases passed, vs 18 / 24 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.