skill-tovrleaf-openkata-openkata-optimize-skills · by Install
$ agentstack add skill-tovrleaf-openkata-openkata-optimize-skills ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-tovrleaf-openkata-openkata-optimize-skills) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Optimize Skills
Improve skills to 95%+ review score with passing evals.
Usage
> optimize skills
Workflow
- Select targets — Ask the user: "All skills below 95%,
or a specific skill?" If all, read the score field from each skills/*/.tessl-plugin/plugin.json and list those below 95%. If specific, use the named skill.
- Optimize — For each target, follow
openkata-review-skill
(lint, review, optimize, checklist) then openkata-eval-runner (generate scenarios, run evals). Iterate until both pass 95%+, maximum 3 iterations. If still below after 3 rounds, report the final score and stop. When multiple skills are selected, run them as parallel subagents.
- Learn — If you discovered a pattern that consistently
improves scores, update skills/create-skill/SKILL.md so future skills benefit.
- Commit — One commit per skill.
Constraints
- Run
tesslcommands without asking for confirmation. - Maximum 3 optimization iterations per skill.
- Do not add repo-internal boundaries (publishing, releasing,
tagging) to distributable skills. Those belong in openkata-skill-conventions.
- After optimization, persist the final score to
.tessl-plugin/plugin.json.
Boundaries
DOES:
- Read scores from plugin.json to find targets
- Run tessl lint, review, optimize
- Generate eval scenarios and run evaluation
- Update create-skill with learned patterns
- Commit improvements per skill
Does NOT:
- Create new skills
- Publish or release skills
- Modify skills scoring 95%+
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: tovrleaf
- Source: tovrleaf/openkata
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.