Comparison
awesome-prompts vs chatgpt_system_prompt
Verdict
Pick awesome-prompts if awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers; 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.
Markdown twin · awesome-prompts alternatives · chatgpt_system_prompt alternatives
GraphCanon updated 4w
vs
Trust & integrity
| Signal | awesome-prompts | chatgpt_system_prompt |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1mo · github_public_v1 | Very active (0d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1mo · github_public_v1 | Not a fork · Personal account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- awesome-prompts
- Curated chatgpt prompts and advanced prompt engineering papers
- chatgpt_system_prompt
- A collection of GPT system prompts and knowledge on prompt injection leaking
Stars
- awesome-prompts
- 8.4k
- chatgpt_system_prompt
- 11k
Forks
- awesome-prompts
- 798
- chatgpt_system_prompt
- 1.5k
Open issues
- awesome-prompts
- 35
- chatgpt_system_prompt
- 1
Language
- awesome-prompts
- -
- chatgpt_system_prompt
- HTML
Adopt for
- awesome-prompts
- awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers.
- 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.
Persona
- awesome-prompts
- -
- chatgpt_system_prompt
- -
Runtime
- awesome-prompts
- -
- chatgpt_system_prompt
- -
License
- awesome-prompts
- GPL-3.0
- chatgpt_system_prompt
- MIT
Last pushed
- awesome-prompts
- Jul 11, 2026
- chatgpt_system_prompt
- Jul 27, 2026
Categories
- awesome-prompts
- Developer Tools
- chatgpt_system_prompt
- Developer Tools
Trust and health
Open issues (now)
- awesome-prompts
- 35
- chatgpt_system_prompt
- 1
Full report
- awesome-prompts
- Trust report
- chatgpt_system_prompt
- Trust report
Choose awesome-prompts if…
- License: awesome-prompts is GPL-3.0, chatgpt_system_prompt is MIT.
- Tags unique to awesome-prompts: awesome-list, chatgpt, prompt-attack, prompt-protect.
- Need detailed prompt engineering resources
When NOT to use awesome-prompts
- Seeking a platform for generating new prompts rather than reviewing existing ones
- In search of direct support tools or services, not just informational content
- Requiring real-time collaboration on prompt creation and experimentation
Choose chatgpt_system_prompt if…
- License: chatgpt_system_prompt is MIT, awesome-prompts is GPL-3.0.
- Tags unique to chatgpt_system_prompt: gpt.
- 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ai-boost/awesome-prompts) · observed Jul 28, 2026
- GitHub forks (ai-boost/awesome-prompts) · observed Jul 28, 2026
- Last push (ai-boost/awesome-prompts) · observed Jul 11, 2026
- License file (GPL-3.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (LouisShark/chatgpt_system_prompt) · observed Jul 27, 2026
- GitHub forks (LouisShark/chatgpt_system_prompt) · observed Jul 27, 2026
- Last push (LouisShark/chatgpt_system_prompt) · observed Jul 27, 2026
- License file (MIT) · observed Jul 27, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-prompts 8.4k · chatgpt_system_prompt 11k (synced Jul 28, 2026).
Common questions
- What is the difference between awesome-prompts and chatgpt_system_prompt?
- awesome-prompts: Curated chatgpt prompts and advanced prompt engineering papers. chatgpt_system_prompt: A collection of GPT system prompts and knowledge on prompt injection leaking. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-prompts over chatgpt_system_prompt?
- Choose awesome-prompts over chatgpt_system_prompt when License: awesome-prompts is GPL-3.0, chatgpt_system_prompt is MIT; Tags unique to awesome-prompts: awesome-list, chatgpt, prompt-attack, prompt-protect; Need detailed prompt engineering resources.
- When should I choose chatgpt_system_prompt over awesome-prompts?
- Choose chatgpt_system_prompt over awesome-prompts when License: chatgpt_system_prompt is MIT, awesome-prompts is GPL-3.0; Tags unique to chatgpt_system_prompt: gpt; When working with GPT models, you seek direct examples and guidance related to secure prompt design.
- When should I avoid awesome-prompts?
- Seeking a platform for generating new prompts rather than reviewing existing ones In search of direct support tools or services, not just informational content Requiring real-time collaboration on prompt creation and experimentation
- 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
- Is awesome-prompts or chatgpt_system_prompt more popular on GitHub?
- chatgpt_system_prompt has more GitHub stars (10,699 vs 8,440). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-prompts and chatgpt_system_prompt open source?
- Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, chatgpt_system_prompt: MIT).
- Where can I find alternatives to awesome-prompts or chatgpt_system_prompt?
- GraphCanon lists graph-backed alternatives at awesome-prompts alternatives and chatgpt_system_prompt alternatives (awesome-prompts markdown twin, chatgpt_system_prompt 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, awesome-prompts or chatgpt_system_prompt?
- awesome-prompts: Very active. chatgpt_system_prompt: 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 awesome-prompts and chatgpt_system_prompt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-prompts trust report; chatgpt_system_prompt trust report.