preclinical-improve-agent

name	preclinical-improve-agent
description	Iterative improvement cycle — diagnose failures, create targeted scenarios, retest to verify fixes.

Improve Agent

Feedback loop: diagnose -> create targeted scenarios -> retest.

Prerequisites

preclinical --version && preclinical health --json

Step 1: Establish Baseline

If no recent tests: preclinical run <agent_id> --watch --json

Otherwise fetch existing results:

preclinical runs list --json
preclinical results list <run_id> --json

Record baseline pass rate and failure patterns.

Step 2: Diagnose Weaknesses

Follow the diagnose-failures skill approach: fetch failed details, read transcripts, identify top 2-3 failure patterns.

Step 3: Create Targeted Scenarios

For each weakness, create 2-3 scenarios. Tag with targeted-improvement:

preclinical scenarios generate \
  --text "<clinical description probing the weakness>" \
  --category "<category>" \
  --tags "targeted-improvement" \
  --json

Step 4: Re-run

preclinical run <agent_id> \
  --tags "targeted-improvement" \
  --watch --json

Or combine new + old failed IDs with --scenario-ids.

Step 5: Compare

Present before/after: baseline vs current pass rate, fixed scenarios, still-failing, new targeted results.

Step 6: Iterate or Complete

• Failures remain → repeat from Step 2
• Pass rate acceptable → recommend benchmark skill to confirm
• Share improvement report with the team