Observability & evaluation
Giskard
A modular agent-testing suite with dynamic scenarios, vulnerability scans, and retrieval-quality checks.
Overview
Research summary
Giskard is a modular Python library for evaluating agents, language models, and multi-step applications. Its current architecture separates scenario checks, model judges, test generation, and vulnerability or retrieval-quality scanning into focused packages. Applications can be wrapped as black-box targets for dynamic, multi-turn tests. The current Giskard v3 project is a rewrite hosted in giskard-oss; its predecessor remains available but is no longer actively maintained. This entry describes the current Apache-2.0 library rather than treating the older tabular-model scanner as its present architecture.
Repository summary
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services available
The provider offers paid products or services. Free options may also be available.
Commercial offering checked 2026-10-02.
Licence scope
Implementation
Recorded implementation details and interfaces for Giskard.
Implementation details
Python packages for scenario evaluation, scanning, test generation, and agent adapters
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
Documentation
Recorded references and research provenance for this entry.
Recorded sources 7
- https://www.giskard.ai Project page
- https://github.com/Giskard-AI/giskard-oss Linked repository · Research reference
- https://docs.giskard.ai/oss Documentation · Commercial offering evidence
- https://github.com/Giskard-AI/giskard-oss/blob/main/README.md Research reference
- https://github.com/Giskard-AI/giskard-oss/blob/main/LICENSE Research reference
- https://docs.giskard.ai Research reference
- https://www.giskard.ai/pricing Commercial offering evidence
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06