--- title: "iFixAi vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ifixai-ai-ifixai-vs-sindresorhus-awesome" tools: ["ifixai-ai-ifixai", "sindresorhus-awesome"] --- # iFixAi vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick iFixAi when license: iFixAi is Apache-2.0, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, iFixAi is Apache-2.0. [iFixAi](https://www.ifixai.ai) reports 1.3k GitHub stars, 170 forks, and 0 open issues, last pushed Jul 8, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [iFixAi's repository](https://github.com/ifixai-ai/iFixAi) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [iFixAi](/tools/ifixai-ai-ifixai.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | Catch your AI's mistakes and blind spots before your customers or regulators do. iFixAi runs 45 inspections, 32 graded core plus 13 extended for frontier risks like sabotage, sandbagging, and oversigh | 😎 Curated list of awesome topics including hardware resources | | Stars | 1,342 | 484,026 | | Forks | 170 | 35,799 | | Open issues | 0 | 92 | | Language | Python | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | CC0-1.0 | | Categories | AI Agents, Computer Vision, LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [iFixAi](/tools/ifixai-ai-ifixai.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 3d | 11d | | Open issues (now) | 0 | 92 | | Owner type | Organization | User | | Full report | [trust report](/tools/ifixai-ai-ifixai/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Choose when ### Choose iFixAi if… - License: iFixAi is Apache-2.0, awesome is CC0-1.0. - Tags unique to iFixAi: agent-evaluation, ai, ai evaluation, ai-alignment. - Also covers AI Agents, Computer Vision. ### Choose awesome if… - License: awesome is CC0-1.0, iFixAi is Apache-2.0. - Tags unique to awesome: awesome-list, resources. - More GitHub stars (484k vs 1.3k) - visibility, not fit. ## When NOT to use iFixAi - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use awesome - 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 iFixAi and awesome? iFixAi: Catch your AI's mistakes and blind spots before your customers or regulators do. iFixAi runs 45 inspections, 32 graded core plus 13 extended for frontier risks like sabotage, sandbagging, and oversigh. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose iFixAi over awesome? Choose iFixAi over awesome when License: iFixAi is Apache-2.0, awesome is CC0-1.0; Tags unique to iFixAi: agent-evaluation, ai, ai evaluation, ai-alignment; Also covers AI Agents, Computer Vision. ### When should I choose awesome over iFixAi? Choose awesome over iFixAi when License: awesome is CC0-1.0, iFixAi is Apache-2.0; Tags unique to awesome: awesome-list, resources; More GitHub stars (484k vs 1.3k) - visibility, not fit. ### When should I avoid iFixAi? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid awesome? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is iFixAi or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 1,342). Stars measure visibility, not whether either tool fits your constraints. ### Are iFixAi and awesome open source? Yes - both are open-source projects on GitHub (iFixAi: Apache-2.0, awesome: CC0-1.0). ### Where can I find alternatives to iFixAi or awesome? GraphCanon lists graph-backed alternatives at [iFixAi alternatives](/tools/ifixai-ai-ifixai/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([iFixAi markdown twin](/tools/ifixai-ai-ifixai/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/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/ifixai-ai-ifixai-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, iFixAi or awesome? iFixAi: Very active. awesome: 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 iFixAi and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [iFixAi trust report](/tools/ifixai-ai-ifixai/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ifixai-ai-ifixai`](/api/graphcanon/graph?tool=ifixai-ai-ifixai) - 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/_