5 Key Metrics Every AI Agent Dashboard Should Display

A dashboard that shows too much is almost as useless as one that shows nothing. When your team opens the Mission Control, they should immediately understand the health of your agent fleet — without reading a single log line. These five metrics make that possible.

1. Task Success Rate

What It Tells You

The percentage of tasks your agents complete successfully. This is the single most important number on your dashboard. If it is high, things are working. If it drops, something needs attention.

Why It Matters

A success rate below 95% means roughly one in twenty tasks is failing. Depending on your volume, that could be hundreds of failures per day. Without this metric visible on your dashboard, those failures are invisible until a customer complains or a downstream system breaks.

What to Watch For

• **Gradual decline**: Often indicates an external API degradation, model drift, or data quality issue
• **Sudden drop**: Usually points to a configuration change, deployment issue, or external service outage
• **Inconsistency by agent**: If one agent's success rate is much lower than others, that specific agent may need attention

Dashboard Display

Show this as a large, prominent number with a color indicator — green above 95%, yellow between 90-95%, red below 90%. Include a 24-hour trend line so you can see whether it is improving or deteriorating.

2. Active Agents and Their Status

What It Tells You

How many agents are currently running, and are they healthy? This is your fleet overview — the "are the lights on" check.

Why It Matters

Agents can go offline for many reasons — infrastructure issues, configuration errors, resource exhaustion. If three of your ten agents are down, your remaining seven are handling extra load, which affects latency and potentially quality.

What to Watch For

• **Agents stuck in "starting" state**: May indicate a deployment or configuration problem
• **Agents repeatedly cycling**: Crashing and restarting is often worse than being fully down — it burns resources without completing work
• **Uneven workload**: Some agents overloaded while others sit idle suggests a routing issue

Dashboard Display

An agent grid where each agent is represented by a card with a clear status indicator. The card should show the agent name, current status (healthy, warning, error, offline), what it is currently working on, and its queue depth.

3. Queue Depth

What It Tells You

How many tasks are waiting to be processed. This is your leading indicator — it tells you about the future, not just the present.

Why It Matters

A growing queue means demand is outpacing your agents' capacity. If unchecked, it leads to increased latency, timeouts, and potentially task failures. Conversely, an empty queue across all boards means your agents may be over-provisioned — costing you money without doing work.

What to Watch For

• **Steadily growing queue**: Your agents cannot keep up. You need more agents or faster processing.
• **Queue spikes at specific times**: Predictable demand patterns that could be addressed with scheduled scaling.
• **Queue stuck at zero**: If you expect work to be coming in and the queue is empty, tasks may not be reaching your boards.

Dashboard Display

Show total queue depth prominently, with a per-board breakdown below it. A simple bar chart showing queue depth over time reveals patterns — daily cycles, unexpected spikes, or concerning trends.

4. Average Task Duration

What It Tells You

How long tasks take from start to completion. This affects user experience if agents serve customers, and it affects throughput if agents process data.

Why It Matters

Increasing task duration is one of the earliest signs of trouble. It can indicate:

• LLM API slowdowns
• Agent logic getting stuck in retry loops
• External tool responses degrading
• Tasks becoming more complex over time

What to Watch For

• **Gradual increase**: Often means something external is slowing down — an API, a database, a third-party service
• **Bimodal distribution**: Tasks are either fast or very slow, suggesting some tasks hit a problematic code path
• **Duration varies by agent**: Points to configuration differences or resource allocation issues

Dashboard Display

Show the average prominently, but also include the P95 (95th percentile) — the duration below which 95% of tasks complete. The P95 catches the outliers that averages hide. A time-series chart showing duration trends over hours or days reveals degradation before it becomes critical.

5. Cost Per Task

What It Tells You

How much each task costs in terms of LLM tokens, API calls, and compute resources. This is your unit economics metric.

Why It Matters

AI agents can be surprisingly expensive if not monitored. A single poorly optimized agent can burn through an LLM budget in hours. Knowing your cost per task lets you:

• Budget accurately for scaling
• Identify agents or task types that need optimization
• Justify the AI investment to finance and leadership
• Catch runaway costs before they become a problem

What to Watch For

• **Rising cost per task**: May indicate agents using more tokens per request (prompt drift, more retries) or external API price changes
• **High variance**: Some tasks costing 10x more than others suggests inconsistent agent behavior
• **Cost not decreasing over time**: As agents learn and improve, cost per task should trend down. If it does not, something may be preventing optimization.

Dashboard Display

Show the average cost per task with a daily total. Break it down by component — LLM tokens, external API calls, compute — so you can see where the money goes. A trend line over the past 30 days shows whether your optimization efforts are paying off.

Putting It All Together

The ideal Mission Control dashboard shows these five metrics at the top of the page, immediately visible when anyone opens it:

| Metric | What It Answers | |--------|----------------| | Success Rate | Are agents working correctly? | | Agent Status | Is the fleet healthy? | | Queue Depth | Can we keep up with demand? | | Task Duration | Are agents fast enough? | | Cost Per Task | Are we spending wisely? |

Everything else — detailed logs, execution traces, configuration settings — lives on deeper pages. But these five numbers give you the health of your entire agent operation at a glance.

Beyond the Big Five

Once you have the essentials covered, consider adding:

• **Error breakdown by type**: Not just how many errors, but what kind — helps prioritize fixes
• **Agent utilization**: Percentage of time each agent is actively working vs. idle — helps with capacity planning
• **Task type distribution**: What kinds of tasks are agents processing most — helps prioritize improvements
• **Trend comparisons**: This week vs. last week for all metrics — shows whether things are getting better or worse

Conclusion

You do not need dozens of metrics cluttering your dashboard. Five well-chosen numbers — success rate, agent status, queue depth, task duration, and cost per task — tell you everything you need to know about your agent fleet's health.

Our [Mission Control templates](/templates) display these metrics prominently, with clean visualizations that your entire team can understand at a glance.