Compare · Agent Infrastructure
author-contributions vs local-ai-agents
Which agent infrastructure piece is right for you?
Notable score gap. local-ai-agents scores meaningfully higher; see individual reviews for nuance.
01 — TL;DR
If you need self-containment above all else, pick local-ai-agents (4.3/5). author-contributions (3.2/5) is a reasonable alternative if you're already in its source ecosystem. They overlap in agent infrastructure piece territory.
Side by side
3.2/5
4.3/5
Where they differ
- Trigger clarity. trigger clarity: author-contributions and local-ai-agents score essentially the same (4.5 vs 4.5). Neither has an edge here.
- Output specificity. output specificity: author-contributions and local-ai-agents score essentially the same (4.0 vs 4.0). Neither has an edge here.
- Scope precision. scope precision: author-contributions and local-ai-agents score essentially the same (4.5 vs 4.5). Neither has an edge here.
- Self-containment. self-containment: local-ai-agents is clearly stronger (4.0 vs 4.5). For workloads where this dimension matters, prefer local-ai-agents.
- Reusability. reusability: author-contributions and local-ai-agents score essentially the same (3.5 vs 3.5). Neither has an edge here.
Which to pick
When to choose author-contributions
- You weight community adoption — author-contributions's upstream repo has 185,014 stars vs 70,070.
- The agent infrastructure piece convention you're working in matches author-contributions's scope.
When to choose local-ai-agents
- Your workload emphasizes self-containment — local-ai-agents scores 4.0 vs 4.5 here.
- The agent infrastructure piece convention you're working in matches local-ai-agents's scope.
Scenario by scenario
| Scenario | Winner | Why |
|---|---|---|
| Agent must auto-select between many agent infrastructure pieces | either | Trigger clarity decides — clearer triggers reduce routing errors. |
| Output must be a specific file format or structured data | either | Output specificity determines whether downstream tools can rely on the result. |
| Skill must be readable and complete out of the box | local-ai-agents | Self-containment matters when you're not the original author. |
| Cross-team or cross-project reuse expected | either | Reusability separates one-off scripts from durable building blocks. |
Common questions
- Which is better, author-contributions or local-ai-agents?
- local-ai-agents ranks higher overall (4.3 vs 3.2 on our 0–5 rubric). That said, the better choice depends on which dimensions matter most for your use case.
- Are author-contributions and local-ai-agents both free to use?
- Both skills are free and open-source (or freely licensed). author-contributions: See source repo. local-ai-agents: See source repo. Installation has no cost; usage costs depend on the underlying LLM tokens consumed when you invoke the skill.
- Can I install both author-contributions and local-ai-agents at the same time?
- Yes. Agent skills are not exclusive — an agent runtime (Claude Code, Codex, etc.) can have many skills installed and route to whichever matches the current task. Installing both is a low-cost way to keep your options open.
- Where do these skills come from?
- author-contributions is sourced from skillsmp.com (curated marketplace). local-ai-agents is sourced from skillsmp.com (curated marketplace). We verify each skill across multiple sources where possible; author-contributions appears in 1 source, local-ai-agents in 1.