The number of "AI agents" on the market went from a handful to thousands in under two years. Almost every one of them claims to be autonomous, to "do the work for you," to replace a role. Most buyers have no reliable way to tell a genuinely capable agent from a well-funded demo.
This guide gives you the six signals we use at Electra Index to separate the two — and how to check each one in a few minutes.
1. What it actually does, not what it claims
"Autonomous AI agent" means nothing on its own. The useful question is: which concrete tasks does it complete end to end, without a human finishing the job?
Read the product's own documentation and look for named, verifiable capabilities — "books meetings on your calendar," "opens and merges pull requests," "answers tickets and closes them" — rather than adjectives. An agent that lists ten vague superpowers and zero concrete workflows is usually a wrapper around a chat box.
On Electra, every agent's capabilities are listed from its own site, and you can browse agents by what they do rather than by marketing category.
2. Price transparency
A serious product tells you what it costs. The fastest trust signal in this whole market is simply whether a vendor publishes pricing at all.
Watch for three patterns: a clear self-serve price (best), "contact us for a quote" (normal for enterprise, but you can't compare), and a price hidden behind a mandatory demo or a trial wall (a yellow flag). None of these is disqualifying, but opacity should lower your confidence, not raise it.
We track whether each agent's price is published and verified, so you can compare two agents side by side on real numbers instead of sales calls.
3. Trust: declared vs verified vs proven
Not all claims are equal. We grade every fact on three levels:
- Declared — the vendor says so, and nothing more.
- Verified — we confirmed it from a public, dated source.
- Proven — it held up when measured over time.
When you evaluate an agent yourself, apply the same ladder. A capability a vendor merely declares is a starting point for questions, not a reason to buy. Ask for a reference, a case study with numbers, or a trial where you can test the exact workflow you care about. Our full method is on the methodology page.
4. Integrations and an API
An agent is only as useful as the tools it can reach. Before you commit, check that it connects to the systems where your work actually lives — your CRM, your calendar, your codebase, your help desk.
Two specific things to look for: a public API (so the agent fits your stack, not the other way around) and, increasingly, MCP support (the emerging standard that lets agents and tools talk to each other). An agent with neither is an island.
5. Human oversight and control
The best agents are not the ones that ask permission for nothing. They're the ones that let you decide where the guardrails go: what runs automatically, what needs approval, and how to see and undo what the agent did.
Before rolling one out, ask: can I review actions before they happen? Is there an audit log? Can I set limits? An agent you can't supervise is a liability the first time it's wrong at scale.
6. Freshness — is anyone still maintaining it?
The agent space moves weekly. A product that hasn't shipped, updated its docs, or changed its pricing in six months is often quietly abandoned. Freshness is a real quality signal, which is why we timestamp every fact and re-check agents on a schedule — "no source, no claim; no recent source, lower confidence."
Putting it together
No single signal decides it. A cheap agent with no API may be perfect for a solo founder; an expensive, enterprise-only one may be right for a regulated team. The point is to score each option on the same six axes instead of on whoever ran the slickest demo.
That's exactly what Electra Index is for. Start from a category — Sales, Customer Support, Coding — see the agents ranked on quality, price and trust, then put any two head to head. Every number has a source and a date.