Home/Compare/HuChenFeng vs Awesome-Prompt-Engineering

Comparison

HuChenFeng vs Awesome-Prompt-Engineering

Verdict

Pick HuChenFeng when license: HuChenFeng is MIT, Awesome-Prompt-Engineering is Apache-2.0; pick Awesome-Prompt-Engineering when license: Awesome-Prompt-Engineering is Apache-2.0, HuChenFeng is MIT.

Markdown twin · HuChenFeng alternatives · Awesome-Prompt-Engineering alternatives

GraphCanon updated today

HuChenFeng logo

HuChenFeng

Olcmyk/HuChenFeng

1.6kpushed Feb 17, 2026
vs
Awesome-Prompt-Engineering logo

Awesome-Prompt-Engineering

promptslab/Awesome-Prompt-Engineering

6.2kpushed Jul 11, 2026

Trust & integrity

SignalHuChenFengAwesome-Prompt-Engineering
Maintenance
Slowing (144d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none

Tagline

HuChenFeng
收集户晨风的所有内容
Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

Stars

HuChenFeng
1.6k
Awesome-Prompt-Engineering
6.2k

Forks

HuChenFeng
180
Awesome-Prompt-Engineering
723

Open issues

HuChenFeng
23
Awesome-Prompt-Engineering
88

Language

HuChenFeng
-
Awesome-Prompt-Engineering
TypeScript

Adopt for

HuChenFeng
-
Awesome-Prompt-Engineering
-

Persona

HuChenFeng
-
Awesome-Prompt-Engineering
-

Runtime

HuChenFeng
-
Awesome-Prompt-Engineering
-

License

HuChenFeng
MIT
Awesome-Prompt-Engineering
Apache-2.0

Last pushed

HuChenFeng
Feb 17, 2026
Awesome-Prompt-Engineering
Jul 11, 2026

Categories

HuChenFeng
Speech & Audio
Awesome-Prompt-Engineering
LLM Frameworks, Model Training, Speech & Audio

Trust and health

Maintenance

HuChenFeng
Slowing (36%)
Awesome-Prompt-Engineering
Very active (96%)

Days since push

HuChenFeng
144d
Awesome-Prompt-Engineering
0d

Open issues (now)

HuChenFeng
23
Awesome-Prompt-Engineering
88

Owner type

HuChenFeng
User
Awesome-Prompt-Engineering
Organization

Full report

HuChenFeng
Trust report
Awesome-Prompt-Engineering
Trust report

Choose HuChenFeng if…

  • License: HuChenFeng is MIT, Awesome-Prompt-Engineering is Apache-2.0.
  • Tags unique to HuChenFeng: archiving, content-analysis, datasets, internet-culture.
  • Leaner open-issue backlog (23).

When NOT to use HuChenFeng

  • Last GitHub push was 145 days ago (slowing maintenance, Feb 17, 2026). Validate activity before betting a new project on HuChenFeng.

Choose Awesome-Prompt-Engineering if…

  • License: Awesome-Prompt-Engineering is Apache-2.0, HuChenFeng is MIT.
  • Tags unique to Awesome-Prompt-Engineering: chatgpt, chatgpt-api, deep-learning, few-shot-learning.
  • Also covers LLM Frameworks, Model Training.

When NOT to use Awesome-Prompt-Engineering

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: HuChenFeng 1.6k · Awesome-Prompt-Engineering 6.2k (synced Jul 11, 2026).

Common questions

What is the difference between HuChenFeng and Awesome-Prompt-Engineering?
HuChenFeng: 收集户晨风的所有内容. Awesome-Prompt-Engineering: This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc. See the comparison table for live GitHub stats and shared categories.
When should I choose HuChenFeng over Awesome-Prompt-Engineering?
Choose HuChenFeng over Awesome-Prompt-Engineering when License: HuChenFeng is MIT, Awesome-Prompt-Engineering is Apache-2.0; Tags unique to HuChenFeng: archiving, content-analysis, datasets, internet-culture; Leaner open-issue backlog (23).
When should I choose Awesome-Prompt-Engineering over HuChenFeng?
Choose Awesome-Prompt-Engineering over HuChenFeng when License: Awesome-Prompt-Engineering is Apache-2.0, HuChenFeng is MIT; Tags unique to Awesome-Prompt-Engineering: chatgpt, chatgpt-api, deep-learning, few-shot-learning; Also covers LLM Frameworks, Model Training.
When should I avoid HuChenFeng?
Last GitHub push was 145 days ago (slowing maintenance, Feb 17, 2026). Validate activity before betting a new project on HuChenFeng.
When should I avoid Awesome-Prompt-Engineering?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is HuChenFeng or Awesome-Prompt-Engineering more popular on GitHub?
Awesome-Prompt-Engineering has more GitHub stars (6,150 vs 1,630). Stars measure visibility, not whether either tool fits your constraints.
Are HuChenFeng and Awesome-Prompt-Engineering open source?
Yes - both are open-source projects on GitHub (HuChenFeng: MIT, Awesome-Prompt-Engineering: Apache-2.0).
Where can I find alternatives to HuChenFeng or Awesome-Prompt-Engineering?
GraphCanon lists graph-backed alternatives at HuChenFeng alternatives and Awesome-Prompt-Engineering alternatives (HuChenFeng markdown twin, Awesome-Prompt-Engineering 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, HuChenFeng or Awesome-Prompt-Engineering?
HuChenFeng: Slowing. Awesome-Prompt-Engineering: 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 HuChenFeng and Awesome-Prompt-Engineering?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: HuChenFeng trust report; Awesome-Prompt-Engineering trust report.