--- title: "anti-lie vs moby" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lc198707-anti-lie-vs-moby-moby" tools: ["lc198707-anti-lie", "moby-moby"] --- # anti-lie vs moby *GraphCanon updated Jul 15, 2026* ## Verdict Pick anti-lie when anti-lie is primarily Python; moby is Go; pick moby when moby is primarily Go; anti-lie is Python. [anti-lie](https://github.com/lc198707/anti-lie) reports 89 GitHub stars, 7 forks, and 0 open issues, last pushed May 10, 2026. [moby](https://mobyproject.org/) has 72k stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [anti-lie's repository](https://github.com/lc198707/anti-lie) and [moby's repository](https://github.com/moby/moby). | | [anti-lie](/tools/lc198707-anti-lie.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Tagline | Don't make LLMs honest. Make every factual claim auditable., An LLM Claim Auditing Layer with T1-T7 truth gradients. 98.1% business effectiveness on LiarBench v0.2. | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | | Stars | 89 | 71,899 | | Forks | 7 | 19,126 | | Open issues | 0 | 3,821 | | Language | Python | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | AI Agents, Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [anti-lie](/tools/lc198707-anti-lie.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 65d | 1d | | Open issues (now) | 0 | 3.8k | | Owner type | User | Organization | | Full report | [trust report](/tools/lc198707-anti-lie/trust.md) | [trust report](/tools/moby-moby/trust.md) | ## Choose when ### Choose anti-lie if… - anti-lie is primarily Python; moby is Go. - License: anti-lie is Other, moby is Apache-2.0. - Tags unique to anti-lie: agent-skills, ai-safety, anti-lie, audit. - Also covers AI Agents. ### Choose moby if… - moby is primarily Go; anti-lie is Python. - License: moby is Apache-2.0, anti-lie is Other. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. - moby ships Docker support for self-hosted deployment. ## When NOT to use anti-lie - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between anti-lie and moby? anti-lie: Don't make LLMs honest. Make every factual claim auditable., An LLM Claim Auditing Layer with T1-T7 truth gradients. 98.1% business effectiveness on LiarBench v0.2.. moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose anti-lie over moby? Choose anti-lie over moby when anti-lie is primarily Python; moby is Go; License: anti-lie is Other, moby is Apache-2.0; Tags unique to anti-lie: agent-skills, ai-safety, anti-lie, audit; Also covers AI Agents. ### When should I choose moby over anti-lie? Choose moby over anti-lie when moby is primarily Go; anti-lie is Python; License: moby is Apache-2.0, anti-lie is Other; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools; moby ships Docker support for self-hosted deployment. ### When should I avoid anti-lie? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is anti-lie or moby more popular on GitHub? moby has more GitHub stars (71,899 vs 89). Stars measure visibility, not whether either tool fits your constraints. ### Are anti-lie and moby open source? Yes - both are open-source projects on GitHub (anti-lie: Other, moby: Apache-2.0). ### Where can I find alternatives to anti-lie or moby? GraphCanon lists graph-backed alternatives at [anti-lie alternatives](/tools/lc198707-anti-lie/alternatives) and [moby alternatives](/tools/moby-moby/alternatives) ([anti-lie markdown twin](/tools/lc198707-anti-lie/alternatives.md), [moby markdown twin](/tools/moby-moby/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/lc198707-anti-lie-vs-moby-moby.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, anti-lie or moby? anti-lie: Steady. moby: Very active. 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 anti-lie and moby? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [anti-lie trust report](/tools/lc198707-anti-lie/trust); [moby trust report](/tools/moby-moby/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lc198707-anti-lie`](/api/graphcanon/graph?tool=lc198707-anti-lie) - 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/_