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Comparison
Agents Shipgate vs LLM evals
Evals answer whether a model behaved correctly on examples. Agents Shipgate answers whether the released tool surface is reviewable.
Use evals for behavior
LLM eval tools are the right place to test prompts, completions, routing, regressions, and model behavior against written scenarios. They are usually dynamic and scenario-driven.
Use Agents Shipgate for release readiness
Agents Shipgate reads the static release artifact: manifest, tool schemas, scopes, approval policies, side-effect evidence, and idempotency evidence. It runs before promotion and does not invoke the model.
| Question | Evals | Agents Shipgate |
|---|---|---|
| Did the agent answer correctly? | Yes | No |
| What tools are being released? | No | Yes |
| Are high-risk tools missing approval policies? | No | Yes |
| Should this run in CI before promotion? | Often | Yes |
The practical pattern is not either/or: keep evals in the development loop and run Agents Shipgate as a PR-time release gate.
See also
- Agents Shipgate vs Braintrust — hosted eval and observability platform vs local static release gate.
- Agents Shipgate vs LangSmith — LangChain-first runtime traces vs framework-agnostic pre-release review.
- Agents Shipgate vs promptfoo — open-source prompt eval CLI vs static tool-surface manifest review.