Your agents run whatever you hand them, even a half-baked one-liner. Litmusify reads each prompt on-device in under a millisecond and pulls the shaky ones aside before they spiral into a thousand-call mess.
it slips in front of the coding agents your team already runs
Nobody selling you tokens has a reason to help you use fewer. One vague instruction fans out: your agent ransacks the repo, guesses wrong, and tries again. And again.
Illustrative scenario.
No big model in the way. A small classifier on your machine reads each prompt in a millisecond, weighing your instruction and never your code. Your best engineers never feel it.
Local classifiers read structure and specificity to score the prompt. No generative call, no waiting.
< 1 ms · on localhostBelow the bar, the prompt is paused and coached right in your IDE, not thrown as an error.
native chat UITightened, it streams straight to the model. Litmusify trains the human as the work ships.
zero added latencyA tiny daemon on localhost catches each prompt right before it leaves for the network. Clean ones sail through; shaky ones loop back for a quick fix. Your code never goes anywhere.
Your VP won't act on an average score. So we tie it to your merged PRs: the real compute cost of every shipped pull request, before and after.
Illustrative figures.
Nobody likes being audited, so we flipped it. Everyone starts on the cheap models. Write clean prompts and your litmus score climbs, unlocking higher limits and the best frontier models by default.
It's not a race to burn the most tokens. We rank your team by how clearly they ask, tied straight to cost per PR. Clarity rises, waste sinks.
Sample team data.
A gateway can count your tokens. It can't see what you meant. We learn from the one signal nobody else has: which prompts ended in a clean merge, and which spiralled. Every prompt sharpens the next call.
Infra gateways clone an API proxy in weeks. They can't clone the data.
Illustrative figures.
The classifiers, embeddings, and scoring all run on your machine or in your VPC. No one else reads a word, so there's nothing for your security team to sign off on.
What engineers and their VPs ask before they let us near the agents.
No. Classifiers, embeddings, and scoring all run as a local proxy on your machine or in your VPC. Only anonymized telemetry ever syncs: the litmus score, token counts, and detour rate. Your raw prompts and source are never transmitted, so there's nothing for a security team to review.
Lightweight local models (think XGBoost and a small PyTorch classifier, not a frontier LLM) read structural signals: target specificity, action verbs, acceptance criteria, and vector distance from known-good prompts. Those features produce a probabilistic 0–100 score in well under a millisecond.
No. There's no LLM in the hot path. Local classifiers score the prompt in under a millisecond, so a well-formed prompt passes straight through with no perceptible latency.
Rarely. The score is an exponentially-weighted moving average with session inertia, so early exploratory turns barely move it and one-off shorthand on a senior's profile sails through. Only sustained ambiguity trips a detour, and even then it coaches rather than blocks.
Never a hard block. Litmusify uses a soft detour: it pauses an ambiguous prompt and returns a coaching note rendered natively in your IDE. Tighten the prompt and it's released instantly. No error codes, no broken flow.
Anything that speaks MCP or an OpenAI-compatible API: Cursor, Claude Code, Roo Code, Devin, Windsurf, and more, in front of any frontier model. It runs as a local proxy, so it sits in front of the agents without changing your setup.
About five minutes. Drop in the local daemon, point your IDE's base URL (or MCP server) at localhost, and it starts scoring. A file-watcher keeps the config pinned so nobody drifts off the proxy by accident.
The dashboard cross-references the anonymized telemetry with your version control to compute compute cost per merged PR, the one metric leadership can act on. Not a subjective "litmus score 74", just dollars per shipped PR, before and after.
Yes. The whole stack runs inside your VPC with no raw data leaving the perimeter, which is exactly what InfoSec wants to hear. Team and enterprise plans add the shared dashboard, SSO, and PR-level reporting. Free for solo developers.
Two women building the guardrails for the agentic era. We sat beside the engineers, watched the spend spiral from a single lazy prompt, and built the litmus test we wished we'd had.
Headshots coming soon.
Tell us where it's burning and we'll help you put it out. Leave your email below, or just reach a founder directly at aditi@litmusify.com.