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Get Started Free →majiayu000/script-kit-agent-workflow
Autonomous fix-verify workflow for Script Kit GPUI.
Passed 15 of 18 test cases with the skill, and 7 of 18 without it.
and 8 more in the full report
11 fixed7 passed either way3 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
Where are local task issues and session context beads tracked on disk within this repository?
| Checked | Without skill | With skill |
|---|---|---|
| References .hive/issues.jsonl for checking tasks and issue context | Missed | Passed |
The instructions your model reads when the skill loads.
Mandatory workflow for all code changes. Do NOT ask users to test. Do NOT skip verification.
.hive/issues.jsonl for tasks/contextcorrelation_id in all log entries/spanscargo check && cargo clippy --all-targets -- -D warnings && cargo test1. EXPLORE: Understand the problem
- Use Task tool with explore agent for codebase search
- Read relevant files, identify root cause before coding
2. FIX: Make the code change
- Keep changes minimal and focused
3. BUILD: Compile and verify
cargo check && cargo clippy --all-targets -- -D warnings
4. LAUNCH: Run the app with logging
echo '{"type":"show"}' | SCRIPT_KIT_AI_LOG=1 ./target/debug/script-kit-gpui 2>&1
5. CHECK LOGS: Verify the fix
grep -i "keyword" ~/.scriptkit/logs/script-kit-gpui.jsonl
6. VISUAL VERIFY (if UI change):
- Write test script with captureScreenshot()
- Save PNG to ./test-screenshots/
- READ the PNG file to actually verify
7. RUN TESTS: cargo test
test cases passed, vs 7 / 18 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.