Comparison
awesome-prompts vs Awesome-Prompt-Engineering
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 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 · awesome-prompts alternatives · Awesome-Prompt-Engineering alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | awesome-prompts | Awesome-Prompt-Engineering |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1mo · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1mo · github_public_v1 | Not a fork · Organization account As of 3w · 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
- Awesome-Prompt-Engineering
- Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers
Stars
- awesome-prompts
- 8.4k
- Awesome-Prompt-Engineering
- 6.2k
Forks
- awesome-prompts
- 798
- Awesome-Prompt-Engineering
- 734
Open issues
- awesome-prompts
- 35
- Awesome-Prompt-Engineering
- 94
Language
- awesome-prompts
- -
- Awesome-Prompt-Engineering
- TypeScript
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.
- Awesome-Prompt-Engineering
- Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license.
Persona
- awesome-prompts
- -
- Awesome-Prompt-Engineering
- -
Runtime
- awesome-prompts
- -
- Awesome-Prompt-Engineering
- -
License
- awesome-prompts
- GPL-3.0
- Awesome-Prompt-Engineering
- Apache-2.0
Last pushed
- awesome-prompts
- Jul 11, 2026
- Awesome-Prompt-Engineering
- Jul 27, 2026
Categories
- awesome-prompts
- Developer Tools
- Awesome-Prompt-Engineering
- Developer Tools, Model Training
Trust and health
Open issues (now)
- awesome-prompts
- 35
- Awesome-Prompt-Engineering
- 94
Owner type
- awesome-prompts
- User
- Awesome-Prompt-Engineering
- Organization
Full report
- awesome-prompts
- Trust report
- Awesome-Prompt-Engineering
- Trust report
Choose awesome-prompts if…
- License: awesome-prompts is GPL-3.0, Awesome-Prompt-Engineering is Apache-2.0.
- Tags unique to awesome-prompts: awesome-list, 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 Awesome-Prompt-Engineering if…
- License: Awesome-Prompt-Engineering is Apache-2.0, awesome-prompts is GPL-3.0.
- Tags unique to Awesome-Prompt-Engineering: deep-learning, few-shot-learning, gpt, 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 (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 (promptslab/Awesome-Prompt-Engineering) · observed Jul 28, 2026
- GitHub forks (promptslab/Awesome-Prompt-Engineering) · observed Jul 28, 2026
- Last push (promptslab/Awesome-Prompt-Engineering) · observed Jul 27, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-prompts 8.4k · Awesome-Prompt-Engineering 6.2k (synced Jul 28, 2026).
Common questions
- What is the difference between awesome-prompts and Awesome-Prompt-Engineering?
- awesome-prompts: Curated chatgpt prompts and advanced prompt engineering papers. 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 awesome-prompts over Awesome-Prompt-Engineering?
- Choose awesome-prompts over Awesome-Prompt-Engineering when License: awesome-prompts is GPL-3.0, Awesome-Prompt-Engineering is Apache-2.0; Tags unique to awesome-prompts: awesome-list, prompt-attack, prompt-protect; Need detailed prompt engineering resources.
- When should I choose Awesome-Prompt-Engineering over awesome-prompts?
- Choose Awesome-Prompt-Engineering over awesome-prompts when License: Awesome-Prompt-Engineering is Apache-2.0, awesome-prompts is GPL-3.0; Tags unique to Awesome-Prompt-Engineering: deep-learning, few-shot-learning, gpt, machine-learning; Also covers Model Training; You need focused materials on GPT and related models for prompt engineering.
- 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 Awesome-Prompt-Engineering?
- The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering
- Is awesome-prompts or Awesome-Prompt-Engineering more popular on GitHub?
- awesome-prompts has more GitHub stars (8,440 vs 6,197). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-prompts and Awesome-Prompt-Engineering open source?
- Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, Awesome-Prompt-Engineering: Apache-2.0).
- Where can I find alternatives to awesome-prompts or Awesome-Prompt-Engineering?
- GraphCanon lists graph-backed alternatives at awesome-prompts alternatives and Awesome-Prompt-Engineering alternatives (awesome-prompts 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, awesome-prompts or Awesome-Prompt-Engineering?
- awesome-prompts: Very 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 awesome-prompts and Awesome-Prompt-Engineering?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-prompts trust report; Awesome-Prompt-Engineering trust report.