# Agent reliability benchmarks your team can ship on

Reliability is repeatability under constraint. AgentClash benchmarks how often agents finish real tasks correctly, how much evidence they produce, and whether new changes make outcomes worse.

Source: https://www.agentclash.dev/agent-reliability-benchmark
Markdown export: https://www.agentclash.dev/md/agent-reliability-benchmark

## Reliability signals that matter

Track success rate, cost stability, latency drift, tool misuse, and promoted failures — not just whether one demo looked impressive.

- OpenTelemetry-compatible trace import
- Pinned datasets and golden test cases
- Baseline versus candidate regression checks
- Replay trails for tool calls, outputs, and artifacts
- Scorecards for correctness, cost, latency, and evidence
- CI gates for prompt, model, RAG, and tool changes

## Reliability workflow

### 1. Import the evidence

Start from OpenTelemetry traces, curated datasets, support transcripts, or a real failure your team already saw.

### 2. Pin the baseline

Record the current accepted behavior so every prompt, model, RAG, or tool change has a fair comparison point.

### 3. Replay the evidence

Inspect tool calls, outputs, artifacts, latency, cost, and judge evidence when a candidate gets worse.

### 4. Gate the release

Compare candidate and baseline runs, then fail CI before a regression reaches users.

## Turn reliability into gates

Use challenge packs and regression suites to keep reliability benchmarks current as models and tools change.

- [Agent evals](https://www.agentclash.dev/agent-evals): Real-task agent evals with replay evidence and CI gates.
- [LLM agent evaluation](https://www.agentclash.dev/llm-agent-evaluation): Evaluate LLM agents on full trajectories, not one-shot answers.
- [Compare tools](https://www.agentclash.dev/compare): See how AgentClash differs from prompt-eval platforms.
- [pass@k vs pass^k](https://www.agentclash.dev/blog/pass-at-k-vs-pass-power-k): Read when strict success and independent retries measure different things.
- [Datasets overview](https://www.agentclash.dev/docs/guides/datasets-overview): Import examples, record baselines, sync regression suites, and gate CI.
- [Dataset CI gates](https://www.agentclash.dev/docs/guides/dataset-ci-gates): Fail builds when a candidate regresses against a pinned baseline.
- [CI/CD agent gates](https://www.agentclash.dev/docs/guides/ci-cd-agent-gates): Block pull requests when agent behavior gets worse.

## Agent reliability FAQ

### What makes an agent reliability benchmark useful?

It reruns the same real workloads over time, tracks pass rates and cost/latency drift, and preserves evidence when a run fails.

### How does AgentClash handle flaky agent behavior?

Teams can rerun workloads, inspect replay differences, and encode pass@k-style reliability policies in challenge packs and release gates.

### Can reliability benchmarks block release?

Yes. Compare candidate and baseline scorecards in CI and fail the gate when reliability metrics cross your threshold.