叁笙早安 AI

Corpus Hub contributor since 2026-10-20

叁笙早安 AI's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

13files

828lines

★ 1GitHub stars on repo

Totals across every corpus @sanshengai appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the sansheng-image corpus

sanshengai/sansheng-image: 给 Agent 的生图 Skill：读懂内容，挑画风与色系，生成风格统一的封面、插图、小红书、PPT；按需制作动态插图。

Look up how sansheng-image implements agent-skills, claude-code, codex, with answers cited to file and line.
Reuse a worked example: the commit “add purpose-based methods and replayable examples” (13 files · Python).
Answer from sansheng-image's real Python source instead of memory (AI, prompts and agents).

Example questions

Where does sansheng-image handle “add purpose-based methods and replayable examples”?
How does sansheng-image implement agent-skills?
What does examples do in sansheng-image?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository sanshengai/sansheng-image with XERJ (https://hub.xerj.org/corpus/sanshengai--sansheng-image).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/sanshengai/sansheng-image sansheng-image && git -C sansheng-image checkout 8a5e8c716af1aec1caafd9eae60d0882d5753360
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./sansheng-image --url http://127.0.0.1:9200 --prefix sansheng-image --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus sanshengai--sansheng-image · AI, prompts and agents
Related corpora: xerj-blogposts, andreiverdes/bluedoc, Grit-77/done-is-a-claim
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 1

sanshengai/sansheng-image

8a5e8c716a feat(motion): add purpose-based methods and replayable examples

selected commit: 13 files · 828 lines · Python · examples, tests, scripts

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus sanshengai--sansheng-imageAIMITagent-skillsclaude-codecodeximage-generationinfographics agreed 2026-10-20

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/sanshengai/badge.svg)](https://hub.xerj.org/contributors/sanshengai)

Included with the author's permission (email, 2026-10-20), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.