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Propose a turbo skill improvement upstream by filing a GitHub issue against the turbo repo.
Passed 8 of 15 test cases with the skill, and 4 of 15 without it.
and 9 more in the full report
10 fixed2 passed either way6 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
The proposal text for the turbo skill fix has been drafted and sanitized. What is the immediate required step before invoking issue creation tools?
| Checked | Without skill | With skill |
|---|---|---|
| Requests explicit user approval on the drafted proposal text before proceeding. | Missed | Passed |
The instructions your model reads when the skill loads.
Propose an improvement to a turbo skill as an issue on tobihagemann/turbo.
Confirm the local repo exists:
test -d ~/.turbo/repo
If it does not, tell the user to run the Turbo setup first and stop.
Detect skills whose installed copy has drifted from the repo baseline:
for skill in ~/.agents/skills/*/; do
name=$(basename "$skill")
repo_dir=~/.turbo/repo/codex/skills/"$name"
[ -d "$repo_dir" ] || continue
diff -rq "$skill" "$repo_dir" >/dev/null 2>&1 && continue
echo "$name"
done
For each drifted skill, read both versions of every file that differs and the single version of every file present on one side only. Classify each hunk and each one-sided file:
request_user_input to confirm classification.When no corrections survive classification, take the proposed change from conversation context instead. When the conversation describes no change either, tell the user there is nothing to contribute and stop.
Present the corrections in a summary table:
| # | Skill | Change Summary |
|---|-------|----------------|
test cases passed, vs 4 / 15 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.