lift
lift is a Backend performance & caching skill for AI agents, published by tkersey in the dotfiles repository on GitHub. Skillspace rates lift C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Performance optimization with measurement-driven latency, throughput, memory/GC, tail, algorithmic, systems, and micro-architectural work; profile evidence, score-gated experiments, behavior proofs, golden oracles, and regression guards. Use for optimize, speed up, reduce p95/p99, increase throughput/QPS, lower CPU/memory/allocations/GC/syscalls/round trips, profiling, bottlenecks, algorithmic improvement, or benchmarked perf passes. Without a runnable workload, operate in labelled UNMEASURED mode with exact benchmark/profiling/proof commands. Prove Zig-only bench_stats/perf_report CLI iteration before shipping.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 63
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
- 97 / 100
- Maturity
- Structured: ships references or scripts
- 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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