skills
anthropics
Public repository for Agent Skills
freestylefly/awesome-gpt-image-2
awesome-gpt-image-2 is a tool for DeepSeek Harness. Prompt as Code | GPT Image 2 / 2.5 prompt and case library, 530+ cases, 20+ industrial-grade templates and reusable Skills, new 2.5 same-prompt comparison section, with full prompts and generation records, continuously updated.

REVIEW SCORECARD
✓ 无Risky检出 · 自动化扫描结果仅供参考,非官方背书
AI DEEP REVIEW
A large, actively maintained prompt and template library for GPT-Image-2, but install and usage details are unclear from
The README shows no tests, CI configuration, or development/install instructions, so engineering rigor cannot be verified from the given information.
No download-and-execute steps, plaintext secrets, or excessive permissions are visible, but the install command is unknown, so a neutral score is given.
It provides 530+ cases, 20+ industrial templates, reusable Skills, and a 2.5 comparison area, addressing a real prompt-engineering pain point.
The repository is not archived, was last updated 2026-09-11, and the README describes ongoing updates and a newly added 2.5 spotlight section.
The README is rich in marketing content, links, and case references, but it lacks a clear installation command and concrete setup instructions for the plugin.
Generated by AI after reading the project README, as a decision aid; neutral scores are given when information is thin. Not an official endorsement.
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VALIDATION LADDER
FAQ
Prompt as Code | GPT Image 2 / 2.5 prompt and case library, 530+ cases, 20+ industrial-grade templates and reusable Skills, new 2.5 same-prompt comparison section, with full prompts and generation records, continuously u
awesome-gpt-image-2 has 31,402 stars and 3,038 forks on GitHub, last updated 2026-09-11.
awesome-gpt-image-2 is distributed under the MIT license.
awesome-gpt-image-2 is listed in the DSH Universe directory as a tool for DeepSeek Harness. This plugin is listed in the DSH Universe directory and covered by its validation pipeline.
CLASSIFICATION EVIDENCE
System reads GitHub Topics first, then compares against the in-site category dictionary and word-root rules. Current match:skills。