Home/Compare/chatgpt_system_prompt vs Awesome-Prompt-Engineering

Comparison

chatgpt_system_prompt vs Awesome-Prompt-Engineering

Verdict

Pick chatgpt_system_prompt if chatgpt_system_prompt is an essential resource for developers specifically using GPT models needing a collection of system prompts alongside education on the critical issue of prompt injection and leaking; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license.

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

GraphCanon updated Sep 20, 2026

16views this month

chatgpt_system_prompt logo

chatgpt_system_prompt

LouisShark/chatgpt_system_prompt

★ 11kpushed Sep 11, 2026
vs
Awesome-Prompt-Engineering logo

Awesome-Prompt-Engineering

promptslab/Awesome-Prompt-Engineering

★ 6.3kpushed Sep 19, 2026

Trust & integrity

Signalchatgpt_system_promptAwesome-Prompt-Engineering
Maintenance
Active (8d since push)
As of Sep 20, 2026 · github_public_v1
Very active (0d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · 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

chatgpt_system_prompt
A collection of GPT system prompts and knowledge on prompt injection leaking
Awesome-Prompt-Engineering
Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers

Stars

chatgpt_system_prompt
11k
Awesome-Prompt-Engineering
6.3k

Forks

chatgpt_system_prompt
1.5k
Awesome-Prompt-Engineering
765

Open issues

chatgpt_system_prompt
1
Awesome-Prompt-Engineering
116

Language

chatgpt_system_prompt
HTML
Awesome-Prompt-Engineering
TypeScript

Adopt for

chatgpt_system_prompt
chatgpt_system_prompt is an essential resource for developers specifically using GPT models needing a collection of system prompts alongside education on the critical issue of prompt injection and leaking.
Awesome-Prompt-Engineering
Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license.

Persona

chatgpt_system_prompt
-
Awesome-Prompt-Engineering
-

Runtime

chatgpt_system_prompt
-
Awesome-Prompt-Engineering
-

License

chatgpt_system_prompt
MIT
Awesome-Prompt-Engineering
Apache-2.0

Last pushed

chatgpt_system_prompt
Sep 11, 2026
Awesome-Prompt-Engineering
Sep 19, 2026

Categories

chatgpt_system_prompt
Developer Tools
Awesome-Prompt-Engineering
Developer Tools, Model Training

Trust and health

Maintenance

chatgpt_system_prompt
Active (82%)
Awesome-Prompt-Engineering
Very active (96%)

Days since push

chatgpt_system_prompt
8d
Awesome-Prompt-Engineering
0d

Open issues (now)

chatgpt_system_prompt
1
Awesome-Prompt-Engineering
116

Stars delta

chatgpt_system_prompt
+72 (30d)
Awesome-Prompt-Engineering
+139 (30d)

Open issues delta

chatgpt_system_prompt
0 (30d)
Awesome-Prompt-Engineering
+22 (30d)

Owner type

chatgpt_system_prompt
User
Awesome-Prompt-Engineering
Organization

Full report

chatgpt_system_prompt
Trust report
Awesome-Prompt-Engineering
Trust report

Choose chatgpt_system_prompt if…

  • chatgpt_system_prompt is primarily HTML; Awesome-Prompt-Engineering is TypeScript.
  • License: chatgpt_system_prompt is MIT, Awesome-Prompt-Engineering is Apache-2.0.
  • When working with GPT models, you seek direct examples and guidance related to secure prompt design

When NOT to use chatgpt_system_prompt

  • For developing or troubleshooting other types of AI models not based on GPT architecture which might have different requirements for system prompts
  • In scenarios where the focus is on learning generic machine learning principles rather than specific to GPT's prompt engineering considerations and limitations

Choose Awesome-Prompt-Engineering if…

  • Awesome-Prompt-Engineering is primarily TypeScript; chatgpt_system_prompt is HTML.
  • License: Awesome-Prompt-Engineering is Apache-2.0, chatgpt_system_prompt is MIT.
  • Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, machine-learning.
  • Also covers Model Training.
  • You need focused materials on GPT and related models for prompt engineering

When NOT to use Awesome-Prompt-Engineering

  • The project requires languages other than TypeScript
  • Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering

Explore

Sources

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

GitHub stars on cards: chatgpt_system_prompt 11k · Awesome-Prompt-Engineering 6.3k (synced Sep 20, 2026).

Common questions

What is the difference between chatgpt_system_prompt and Awesome-Prompt-Engineering?
chatgpt_system_prompt: A collection of GPT system prompts and knowledge on prompt injection leaking. Awesome-Prompt-Engineering: Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers. See the comparison table for live GitHub stats and shared categories.
When should I choose chatgpt_system_prompt over Awesome-Prompt-Engineering?
Choose chatgpt_system_prompt over Awesome-Prompt-Engineering when chatgpt_system_prompt is primarily HTML; Awesome-Prompt-Engineering is TypeScript; License: chatgpt_system_prompt is MIT, Awesome-Prompt-Engineering is Apache-2.0; When working with GPT models, you seek direct examples and guidance related to secure prompt design.
When should I choose Awesome-Prompt-Engineering over chatgpt_system_prompt?
Choose Awesome-Prompt-Engineering over chatgpt_system_prompt when Awesome-Prompt-Engineering is primarily TypeScript; chatgpt_system_prompt is HTML; License: Awesome-Prompt-Engineering is Apache-2.0, chatgpt_system_prompt is MIT; Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, machine-learning; Also covers Model Training; You need focused materials on GPT and related models for prompt engineering.
When should I avoid chatgpt_system_prompt?
For developing or troubleshooting other types of AI models not based on GPT architecture which might have different requirements for system prompts In scenarios where the focus is on learning generic machine learning principles rather than specific to GPT's prompt engineering considerations and limitations
When should I avoid Awesome-Prompt-Engineering?
The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering
Is chatgpt_system_prompt or Awesome-Prompt-Engineering more popular on GitHub?
chatgpt_system_prompt has more GitHub stars (10,771 vs 6,336). Stars measure visibility, not whether either tool fits your constraints.
Are chatgpt_system_prompt and Awesome-Prompt-Engineering open source?
Yes - both are open-source projects on GitHub (chatgpt_system_prompt: MIT, Awesome-Prompt-Engineering: Apache-2.0).
Where can I find alternatives to chatgpt_system_prompt or Awesome-Prompt-Engineering?
GraphCanon lists graph-backed alternatives at chatgpt_system_prompt alternatives and Awesome-Prompt-Engineering alternatives (chatgpt_system_prompt 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, chatgpt_system_prompt or Awesome-Prompt-Engineering?
chatgpt_system_prompt: Active. 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 chatgpt_system_prompt and Awesome-Prompt-Engineering?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: chatgpt_system_prompt trust report; Awesome-Prompt-Engineering trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.