restful-pressure-benchmark
restful-pressure-benchmark is an LLM evaluation & observability skill for AI agents, published by DeepLink-org in the dlinfer repository on GitHub. Skillspace rates restful-pressure-benchmark D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Run RESTful pressure benchmarks with lmdeploy's profile_restful_api.py after starting an lmdeploy API service. Use when Codex needs to choose ShareGPT native-length or random-length workloads, set tokenizer/model/client parameters without hard-coding qwen, compare models or max-batch settings, preserve logs, inspect running batch and KV cache behavior, and report throughput and cache/OOM handling.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 74
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
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- BSD-3-Clause
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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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