| name | optimize-skill-performance-and-instructions |
| description | Run the full optimization cycle for a plugin — review best practices, generate eval scenarios, run BOTH activation evals (does the skill self-activate?) and content evals (does the plugin help solve tasks?), diagnose gaps, fix, and re-run until scores improve. Use when someone says "optimize my skill", "improve my plugin", "run evals", "benchmark my plugin", or wants to measure and improve how well a plugin helps agents solve tasks. |
Optimize
This skill orchestrates optimize-skill-instructions, setup-skill-performance, and optimize-skill-performance into a single end-to-end optimization cycle.
The full cycle takes 1–2 hours depending on how many scenarios and improvement iterations are needed. Set this expectation with the user upfront.
Overview
Review SKILL.md → Apply quick wins → Generate scenarios → Activation check → Content evals → Analyze → Fix → Re-run → Report
└── optimize-skill-instructions ──┘ └─────────── setup-skill-performance ───────────┘ └──────────── optimize-skill-performance ────────────┘
Two distinct eval types run in this cycle:
- Activation eval — observes which skill self-activates per scenario (does NOT force activation). Tests routing/description quality. ~2–3 min.
- Content eval — forces activation, runs baseline vs. with-context, scores the rubric. Tests content quality. ~10–15 min per scenario per agent.
Both apply to every plugin (single-skill and multi-skill alike). The variable is ordering, not whether to run them.
Run labels
Every tessl eval run invocation MUST include --label <run-label> so the run is identifiable in tessl eval list. The label is a short, human-readable description of what the run is about — not a structured ID.
Compose <run-label> from whatever helps you recognise the run later when scanning the list. Typical ingredients:
