--- title: "giskard-oss vs fact-checker" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/giskard-ai-giskard-oss-vs-jagilley-fact-checker" tools: ["giskard-ai-giskard-oss", "jagilley-fact-checker"] --- # giskard-oss vs fact-checker *GraphCanon updated Jul 12, 2026* ## Verdict Pick giskard-oss when giskard-oss is primarily Python; fact-checker is Jupyter Notebook; pick fact-checker when fact-checker is primarily Jupyter Notebook; giskard-oss is Python. [giskard-oss](https://docs.giskard.ai) reports 5.5k GitHub stars, 485 forks, and 70 open issues, last pushed Jul 10, 2026. [fact-checker](https://github.com/jagilley/fact-checker) has 308 stars, 40 forks, and 0 open issues, last pushed Oct 23, 2023. Figures are from public GitHub metadata via [giskard-oss's repository](https://github.com/Giskard-AI/giskard-oss) and [fact-checker's repository](https://github.com/jagilley/fact-checker). | | [giskard-oss](/tools/giskard-ai-giskard-oss.md) | [fact-checker](/tools/jagilley-fact-checker.md) | | --- | --- | --- | | Tagline | 🐢 Open-Source Evaluation & Testing library for LLM Agents | Fact-checking LLM outputs with self-ask | | Stars | 5,505 | 308 | | Forks | 485 | 40 | | Open issues | 70 | 0 | | Language | Python | Jupyter Notebook | | Adopt for | Giskard-OSS is a Python library aimed at evaluating and testing AI agents, particularly language models. It includes modules for scenario-based tests, security scanning, and synthetic data generation. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | - | | Categories | AI Agents, LLM Frameworks, Vector Databases | LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [giskard-oss](/tools/giskard-ai-giskard-oss.md) | [fact-checker](/tools/jagilley-fact-checker.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 991d | | Open issues (now) | 70 | 0 | | Owner type | Organization | User | | Full report | [trust report](/tools/giskard-ai-giskard-oss/trust.md) | [trust report](/tools/jagilley-fact-checker/trust.md) | ## Shared compatibility - **Python**: [giskard-oss](/tools/giskard-ai-giskard-oss.md) - Python runtime; [fact-checker](/tools/jagilley-fact-checker.md) - Python runtime ## Decision facts: giskard-oss - **Requirements:** Requires Python 3.12 or higher. - **Adopt for:** Giskard-OSS is a Python library aimed at evaluating and testing AI agents, particularly language models. It includes modules for scenario-based tests, security scanning, and synthetic data generation. ## Choose when ### Choose giskard-oss if… - giskard-oss is primarily Python; fact-checker is Jupyter Notebook. - Requirements: Requires Python 3.12 or higher.. - Tags unique to giskard-oss: agent-evaluation, ai-red-team, ai-security, ai-testing. - Also covers AI Agents. - - You need an open-source solution specifically designed for testing LLMs with built-in checks and vulnerability scans. ### Choose fact-checker if… - fact-checker is primarily Jupyter Notebook; giskard-oss is Python. - Tags unique to fact-checker: jupyter notebook, python. - Leaner open-issue backlog (0). ## When NOT to use giskard-oss - - If you prefer a tool without any potential telemetry data collection, even though Giskard allows opting out, as it could be seen as potentially intrusive despite safeguards. - - You are working with environments that only support Python versions below 3.12, since Giskard-OSS requires at least Python 3.12. ## When NOT to use fact-checker - Last GitHub push was 992 days ago (dormant maintenance, Oct 23, 2023). Validate activity before betting a new project on fact-checker. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between giskard-oss and fact-checker? giskard-oss: 🐢 Open-Source Evaluation & Testing library for LLM Agents. fact-checker: Fact-checking LLM outputs with self-ask. See the comparison table for live GitHub stats and shared categories. ### When should I choose giskard-oss over fact-checker? Choose giskard-oss over fact-checker when giskard-oss is primarily Python; fact-checker is Jupyter Notebook; Requirements: Requires Python 3.12 or higher.; Tags unique to giskard-oss: agent-evaluation, ai-red-team, ai-security, ai-testing; Also covers AI Agents; - You need an open-source solution specifically designed for testing LLMs with built-in checks and vulnerability scans. ### When should I choose fact-checker over giskard-oss? Choose fact-checker over giskard-oss when fact-checker is primarily Jupyter Notebook; giskard-oss is Python; Tags unique to fact-checker: jupyter notebook, python; Leaner open-issue backlog (0). ### When should I avoid giskard-oss? - If you prefer a tool without any potential telemetry data collection, even though Giskard allows opting out, as it could be seen as potentially intrusive despite safeguards. - You are working with environments that only support Python versions below 3.12, since Giskard-OSS requires at least Python 3.12. ### When should I avoid fact-checker? Last GitHub push was 992 days ago (dormant maintenance, Oct 23, 2023). Validate activity before betting a new project on fact-checker. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is giskard-oss or fact-checker more popular on GitHub? giskard-oss has more GitHub stars (5,505 vs 308). Stars measure visibility, not whether either tool fits your constraints. ### Are giskard-oss and fact-checker open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to giskard-oss or fact-checker? GraphCanon lists graph-backed alternatives at [giskard-oss alternatives](/tools/giskard-ai-giskard-oss/alternatives) and [fact-checker alternatives](/tools/jagilley-fact-checker/alternatives) ([giskard-oss markdown twin](/tools/giskard-ai-giskard-oss/alternatives.md), [fact-checker markdown twin](/tools/jagilley-fact-checker/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/giskard-ai-giskard-oss-vs-jagilley-fact-checker.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, giskard-oss or fact-checker? giskard-oss: Very active. fact-checker: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for giskard-oss and fact-checker? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [giskard-oss trust report](/tools/giskard-ai-giskard-oss/trust); [fact-checker trust report](/tools/jagilley-fact-checker/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=giskard-ai-giskard-oss`](/api/graphcanon/graph?tool=giskard-ai-giskard-oss) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_