Reliability
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.
Candidate
Baseline
Control
replay timeline
ci verdict
Correctness improved, latency within budget, and required artifacts were preserved for review.
agentclash run create --follow
Reliability signals that matter
Built for reviewable agent decisions
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
Workflow
Reliability workflow
Import the evidence
Start from OpenTelemetry traces, curated datasets, support transcripts, or a real failure your team already saw.
Pin the baseline
Record the current accepted behavior so every prompt, model, RAG, or tool change has a fair comparison point.
Replay the evidence
Inspect tool calls, outputs, artifacts, latency, cost, and judge evidence when a candidate gets worse.
Gate the release
Compare candidate and baseline runs, then fail CI before a regression reaches users.
Turn reliability into gates
Bring your first workload into the loop
Use challenge packs and regression suites to keep reliability benchmarks current as models and tools change.
Agent evals
Real-task agent evals with replay evidence and CI gates.
LLM agent evaluation
Evaluate LLM agents on full trajectories, not one-shot answers.
Compare tools
See how AgentClash differs from prompt-eval platforms.
pass@k vs pass^k
Read when strict success and independent retries measure different things.
Datasets overview
Import examples, record baselines, sync regression suites, and gate CI.
Dataset CI gates
Fail builds when a candidate regresses against a pinned baseline.
CI/CD agent gates
Block pull requests when agent behavior gets worse.
FAQ
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.