sirvir-bench
sirvir-bench is an LLM evaluation & observability skill for AI agents, published by SouthpawIN in the sirvir repository on GitHub. Skillspace rates sirvir-bench C (77/100) and it passed the safety scan; the rating is based on static analysis only.
Model benchmarking skill. Wraps `serve bench` and lm-eval-harness to run standardized benchmarks (MMLU, GPQA, SWE-bench, HumanEval, AIME) on local fleet models and monitored API models. Documents the benchmark workflow, score interpretation thresholds, and how benchmark results feed back into tier assignments in model-database.yaml. Complements the turbofit core skill — turbofit launches and serves models, sirvir-bench measures them.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 25
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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