Home/Compare/hello-agents vs SuperPrompt

Comparison

hello-agents vs SuperPrompt

Verdict

Pick hello-agents when requirements: Min 4 GB RAM; Python knowledge assumed; pick SuperPrompt when tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts.

Markdown twin · hello-agents alternatives · SuperPrompt alternatives

GraphCanon updated 1d

hello-agents logo

hello-agents

datawhalechina/hello-agents

65kpushed Jul 10, 2026
vs
SuperPrompt logo

SuperPrompt

NeoVertex1/SuperPrompt

6.4kpushed Apr 26, 2026

Trust & integrity

Signalhello-agentsSuperPrompt
Maintenance
Very active (0d since push)
As of 1d · github_public_v1
Steady (75d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Personal account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No lockfile
As of 1d · none

Tagline

hello-agents
Course on building intelligent agents from scratch
SuperPrompt
SuperPrompt is an attempt to engineer prompts that might help us understand AI agents.

Stars

hello-agents
65k
SuperPrompt
6.4k

Forks

hello-agents
8.1k
SuperPrompt
574

Open issues

hello-agents
144
SuperPrompt
12

Language

hello-agents
Python
SuperPrompt
-

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.
SuperPrompt
-

Persona

hello-agents
-
SuperPrompt
-

Runtime

hello-agents
-
SuperPrompt
-

License

hello-agents
hello-agents is covered under an unconventional license which may require further review before usage.
SuperPrompt
-

Last pushed

hello-agents
Jul 10, 2026
SuperPrompt
Apr 26, 2026

Categories

hello-agents
AI Agents, LLM Frameworks
SuperPrompt
AI Agents, LLM Frameworks

Trust and health

Maintenance

hello-agents
Very active (96%)
SuperPrompt
Steady (60%)

Days since push

hello-agents
0d
SuperPrompt
75d

Open issues (now)

hello-agents
144
SuperPrompt
12

Owner type

hello-agents
Organization
SuperPrompt
User

Full report

hello-agents
Trust report
SuperPrompt
Trust report

Choose hello-agents if…

  • Requirements: Min 4 GB RAM; Python knowledge assumed.
  • Tags unique to hello-agents: agent, llm, 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 SuperPrompt if…

  • Tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts.
  • Leaner open-issue backlog (12).

When NOT to use SuperPrompt

  • 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 on cards: hello-agents 65k · SuperPrompt 6.4k (synced Jul 11, 2026).

Common questions

What is the difference between hello-agents and SuperPrompt?
hello-agents: Course on building intelligent agents from scratch. SuperPrompt: SuperPrompt is an attempt to engineer prompts that might help us understand AI agents.. See the comparison table for live GitHub stats and shared categories.
When should I choose hello-agents over SuperPrompt?
Choose hello-agents over SuperPrompt when Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, 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 SuperPrompt over hello-agents?
Choose SuperPrompt over hello-agents when Tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts; Leaner open-issue backlog (12).
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 SuperPrompt?
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 SuperPrompt more popular on GitHub?
hello-agents has more GitHub stars (65,432 vs 6,419). Stars measure visibility, not whether either tool fits your constraints.
Are hello-agents and SuperPrompt open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to hello-agents or SuperPrompt?
GraphCanon lists graph-backed alternatives at hello-agents alternatives and SuperPrompt alternatives (hello-agents markdown twin, SuperPrompt 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 SuperPrompt?
hello-agents: Very active. SuperPrompt: Steady. 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 SuperPrompt?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hello-agents trust report; SuperPrompt trust report.