# Evaluate research agents with evidence quality

Research agents live or die on sourcing, synthesis, and artifact quality. AgentClash scores whether an agent found the right evidence, cited it correctly, and finished the investigation under budget.

Source: https://www.agentclash.dev/use-cases/research-agent-evaluation
Markdown export: https://www.agentclash.dev/md/use-cases/research-agent-evaluation

## Research eval signals

Measure coverage, citation quality, artifact completeness, and whether the agent stopped with a useful deliverable.

- 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

## Research 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.

## Encode investigations as packs

Turn recurring research workflows into challenge packs so every model or prompt change reruns the same investigation fairly.

- [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.
- [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.

## Research agent evaluation FAQ

### What should research agent evaluation score?

Task completion, evidence quality, artifact completeness, tool discipline, and whether the final synthesis matches the sources collected.

### Can evals include web or file tools?

Yes. Challenge packs define which tools agents may use and which artifacts must be produced for a pass.

### How do teams debug a failed research run?

Replay shows each search, fetch, note, and synthesis step so reviewers can see where the investigation went off track.