Optimize your skills and tiles: review SKILL.md quality, generate eval scenarios, run evals, compare across models, diagnose gaps, and re-run until scores improve.
88
94%
Does it follow best practices?
Impact
88%
1.07xAverage score across 24 eval scenarios
Passed
No known issues
A platform team maintains a growing library of Tessl tiles and needs to reliably benchmark each tile's skill quality across the range of Claude models their customers use. The process is currently done manually — engineers run commands one at a time and lose track of job IDs when multiple models are running. Benchmarks are sometimes kicked off in parallel by mistake, causing noisy results and billing surprises, and when a job fails it often goes unnoticed until the engineer checks back hours later.
The team wants a single, self-contained shell script that automates the full execution phase of a multi-model benchmark: starting all model runs in the correct order, tracking each job, providing links for real-time monitoring, polling until every run finishes, and handling job failures automatically. The tile being benchmarked is located at ./analytics-tile and already has eval scenarios in place.
Produce one file:
benchmark.sh — An executable shell script that runs the full benchmark. It should print progress updates as each job starts and completes. It should exit with a non-zero status if any run cannot be successfully completed even after a retry attempt.The script should be written for bash and should work on a standard Linux environment with the tessl CLI available on PATH.
evals
scenario-1
scenario-2
scenario-3
scenario-4
scenario-5
scenario-6
scenario-7
scenario-8
scenario-9
scenario-10
scenario-11
scenario-12
scenario-13
scenario-14
scenario-15
scenario-16
scenario-17
scenario-18
scenario-19
scenario-20
scenario-21
scenario-22
scenario-23
scenario-24
skills
compare-skill-model-performance
optimize-skill-instructions
references
optimize-skill-performance
optimize-skill-performance-and-instructions