Monitoring Infrastructure Is Not Evaluating the Operator

The short version: omnara

omnara is an AI monitoring platform — it provides broad observability for AI agents. It monitors what your agents are doing: their state, their calls, their health, their behavior. It is excellent at what it does, which is infrastructure monitoring. What it does not do is score the human operator who drives those agents or rank them against anyone.

SigRank is a different thing entirely: an operator scoring system. It reads token telemetry from any AI tool an operator drives, computes the cascade efficiency (Υ Yield), and ranks them globally. omnara monitors the agents; SigRank scores the operator behind them. The agent is the car; the operator is the driver. Both matter. Only one tells you who is winning.

Feature comparison

Why monitoring agents isn't scoring operators

omnara answers "what are my AI agents doing?" That is infrastructure monitoring, not operator evaluation. Two operators can drive healthy agents with identical monitoring dashboards and have wildly different efficiency. One reuses cached context efficiently and produces 30K output tokens; the other re-sends the same context every turn and produces 3K. Same agent health, ten-fold difference in signal. omnara sees the same dashboard either way.

SigRank's headline metric, Υ = cache_read × output / input², measures exactly that gap. It rewards the operator who compounds cached context into output and penalizes the one who burns fresh input without leverage. omnara gives you the agent dashboard; SigRank tells you whether the operator behind it is compounding or burning.

From monitoring to scoring

If you already run omnara for agent monitoring, you have the infrastructure observability. SigRank adds the operator scoring layer that monitoring platforms never had:

npm install -g sigrank
sigrank enroll      # create your operator identity
sigrank submit      # reads logs, scores, signs, publishes

Prefer to inspect before you submit? Run sigrank me --dry-run to see your scored payload locally, or paste your token counts into the /score calculator to compute your Υ Yield, class tier, and compression ratio instantly, no account, no submission, just the numbers.

Frequently asked questions

Is SigRank an omnara alternative?

They evaluate different things. omnara is an AI monitoring platform — it monitors AI agents with broad observability and infrastructure monitoring. SigRank is an operator scoring system — it evaluates the human at the wheel, not the agent they are driving. omnara tells you what your agents are doing; SigRank tells you how efficiently you are driving them. Monitoring infrastructure is not evaluating the operator. You can run both — they solve different problems.

Why is monitoring agents not the same as scoring operators?

Monitoring agents tells you what the AI is doing — is it running, is it healthy, what calls is it making. Scoring operators tells you how efficiently the human is driving the AI — are they compounding cached context or burning fresh input? The agent is the car; the operator is the driver. omnara monitors the car; SigRank scores the driver. A healthy car does not mean a skilled driver. Monitoring infrastructure is not evaluating the human at the wheel.

What does omnara not measure that SigRank does?

omnara monitors AI agent behavior and infrastructure. SigRank derives the cascade architecture from the operator's token telemetry: Υ Yield (is signal compounding or burning?), compression ratio (output per input), SNR (signal density), Leverage (how much cached context amplifies your input), and Velocity (tokens per unit time). omnara tells you what your agents are doing; SigRank tells you whether the operator behind them is compounding or burning.

Can I use both omnara and SigRank?

Yes, and they are complementary. Use omnara to monitor your AI agents and infrastructure health. Use SigRank to score the human operator who drives those agents. The SigRank CLI reads token telemetry locally (token counts only, never agent behavior logs), computes the cascade metrics, signs a snapshot with ed25519, and publishes it to the leaderboard. omnara sees the agents; SigRank scores the operator behind them. Run `sigrank enroll` then `sigrank submit` to get your rank.

What is the difference between agent monitoring and operator scoring?

Agent monitoring (omnara) records what AI agents are doing — their state, their calls, their health, their behavior. It is infrastructure-level observability. Operator scoring (SigRank) aggregates the token telemetry across an operator's entire body of work — across tools, across platforms — and computes a single cascade efficiency score (Υ Yield) that is comparable globally. Monitoring answers 'what are my agents doing?' Scoring answers 'how efficiently does this person drive AI?' The first is observability; the second is competition.