Individual skill
jev-audit
Audit a codebase for LLM calls that are really classifications in disguise, then produce a costed swap plan for a System One model. Use when asked to cut AI inference cost or latency, when scoping a performance engagement for a client, when reviewing an agent loop that feels slow, or when asked "where could we use Jev here". Produces a ranked table of candidates with measured latency and dollar deltas.
jev-audit/SKILL.md
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- agent-skills Repository topic
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# Inference-cost audit
Most production LLM calls return a **label**, not prose — a route, a score, a yes/no, a
category. Those calls pay for autoregressive generation they do not use. This audit finds
them and prices the swap.
Deliverable: a ranked table of candidates with measured deltas. Sellable as a OneWave
engagement; same shape as `marketing-brain` — a repeatable audit run per client.
## 1. Find the candidates
Search for LLM calls, then filter to the ones whose output is a label:
```bash