Comparison
hello-agents vs agents-from-scratch
Verdict
Pick hello-agents when license: hello-agents is Other, agents-from-scratch is MIT; pick agents-from-scratch when license: agents-from-scratch is MIT, hello-agents is Other.
Markdown twin · hello-agents alternatives · agents-from-scratch alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | hello-agents | agents-from-scratch |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4d · github_public_v1 | Slowing (182d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | No lockfile (source not queried) As of today · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- hello-agents
- Course on building intelligent agents from scratch
- agents-from-scratch
- Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning.
Stars
- hello-agents
- 65k
- agents-from-scratch
- 901
Forks
- hello-agents
- 8.1k
- agents-from-scratch
- 226
Open issues
- hello-agents
- 144
- agents-from-scratch
- 6
Language
- hello-agents
- Python
- agents-from-scratch
- Python
Adopt for
- hello-agents
- hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.
- agents-from-scratch
- -
Persona
- hello-agents
- -
- agents-from-scratch
- -
Runtime
- hello-agents
- -
- agents-from-scratch
- -
License
- hello-agents
- hello-agents is covered under an unconventional license which may require further review before usage.
- agents-from-scratch
- MIT
Last pushed
- hello-agents
- Jul 10, 2026
- agents-from-scratch
- Jan 14, 2026
Categories
- hello-agents
- AI Agents, LLM Frameworks
- agents-from-scratch
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- hello-agents
- Very active (96%)
- agents-from-scratch
- Slowing (36%)
Days since push
- hello-agents
- 0d
- agents-from-scratch
- 182d
Open issues (now)
- hello-agents
- 144
- agents-from-scratch
- 6
Owner type
- hello-agents
- Organization
- agents-from-scratch
- User
Full report
- hello-agents
- Trust report
- agents-from-scratch
- Trust report
Choose hello-agents if…
- License: hello-agents is Other, agents-from-scratch is MIT.
- Requirements: Min 4 GB RAM; Python knowledge assumed.
- Tags unique to hello-agents: agent, rag, tutorial.
- You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
When NOT to use hello-agents
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application.
- Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
Choose agents-from-scratch if…
- License: agents-from-scratch is MIT, hello-agents is Other.
- Tags unique to agents-from-scratch: agent-architecture, ai-agents, ai-education, ai-from-scratch.
- Leaner open-issue backlog (6).
When NOT to use agents-from-scratch
- Last GitHub push was 182 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on agents-from-scratch.
- 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (datawhalechina/hello-agents) · observed Jul 11, 2026
- GitHub forks (datawhalechina/hello-agents) · observed Jul 11, 2026
- Last push (datawhalechina/hello-agents) · observed Jul 10, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pguso/agents-from-scratch) · observed Jul 15, 2026
- GitHub forks (pguso/agents-from-scratch) · observed Jul 15, 2026
- Last push (pguso/agents-from-scratch) · observed Jan 14, 2026
- License file (MIT) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: hello-agents 65k · agents-from-scratch 901 (synced Jul 11, 2026).
Common questions
- What is the difference between hello-agents and agents-from-scratch?
- hello-agents: Course on building intelligent agents from scratch. agents-from-scratch: Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning.. See the comparison table for live GitHub stats and shared categories.
- When should I choose hello-agents over agents-from-scratch?
- Choose hello-agents over agents-from-scratch when License: hello-agents is Other, agents-from-scratch is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, rag, tutorial; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
- When should I choose agents-from-scratch over hello-agents?
- Choose agents-from-scratch over hello-agents when License: agents-from-scratch is MIT, hello-agents is Other; Tags unique to agents-from-scratch: agent-architecture, ai-agents, ai-education, ai-from-scratch; Leaner open-issue backlog (6).
- When should I avoid hello-agents?
- Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
- When should I avoid agents-from-scratch?
- Last GitHub push was 182 days ago (slowing maintenance, Jan 14, 2026). Validate activity before betting a new project on agents-from-scratch. 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.
- Is hello-agents or agents-from-scratch more popular on GitHub?
- hello-agents has more GitHub stars (65,432 vs 901). Stars measure visibility, not whether either tool fits your constraints.
- Are hello-agents and agents-from-scratch open source?
- Yes - both are open-source projects on GitHub (hello-agents: Other, agents-from-scratch: MIT).
- Where can I find alternatives to hello-agents or agents-from-scratch?
- GraphCanon lists graph-backed alternatives at hello-agents alternatives and agents-from-scratch alternatives (hello-agents markdown twin, agents-from-scratch markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, hello-agents or agents-from-scratch?
- hello-agents: Very active. agents-from-scratch: Slowing. 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 hello-agents and agents-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; agents-from-scratch trust report.