# Agent evaluation for government and public sector

Public-sector agents need traceable decisions, artifact bundles, and repeatable tests before deployment. AgentClash captures replay evidence and scorecards reviewers can attach to change records.

Source: https://www.agentclash.dev/industries/government
Markdown export: https://www.agentclash.dev/md/industries/government

## Government eval signals

Track task completion, evidence quality, tool discipline, artifact exports, and whether candidate runs regress against an approved baseline.

- 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

## Government eval 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.

## Build audit-ready packs

Encode citizen service workflows as challenge packs with validators and replay links your program office can review.

- [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.
- [Enterprise pilot](https://www.agentclash.dev/enterprise): Discuss residency, deployment, and governed eval for public sector.
- [Agent replay feature](https://www.agentclash.dev/features/agent-replay): Inspect trajectories and artifact bundles after each run.
- [Agent evaluation glossary](https://www.agentclash.dev/glossary/agent-evaluation): Core terms for standing up an eval program.
- [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.

## Government agent evaluation FAQ

### Can reviewers export evidence from a run?

Yes. Replay captures tool calls, artifacts, and scorecard dimensions so reviewers can attach evidence to internal change and approval workflows.

### Does AgentClash guarantee FedRAMP or IL compliance?

No. AgentClash provides evaluation infrastructure and evidence. Deployment, accreditation, and authority to operate decisions are yours. Enterprise can discuss dedicated deployment during architecture review.

### How do teams compare vendors or model routes fairly?

Run every candidate on the same frozen challenge pack with identical tools and budgets, then compare scorecards and replay side by side.