Christian Schröder
Christian Schröder'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.
Totals across every corpus @cwschroeder 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 TensorFold corpus
ashhart/TensorFold: LLM Inference Engine for Metal and CUDA
- Look up how TensorFold implements ai, ai-tools, llm, with answers cited to file and line.
- Reuse a worked example: the commit “Flash Next on Metal: requests on shared sessions sized to the traffic…” (41 files · Zig, Python).
- Answer from TensorFold's real Zig source instead of memory (AI, prompts and agents).
- How does TensorFold implement ai?
- What does zig do in TensorFold?
Search the GitHub repository ashhart/TensorFold with XERJ (https://hub.xerj.org/corpus/ashhart--tensorfold). 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/ashhart/TensorFold TensorFold && git -C TensorFold checkout d58765718a0e1a0524a64fa04510d4b3cfef815b 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./TensorFold --url http://127.0.0.1:9200 --prefix tensorfold --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: Apache-2.0. Keep the copyright notice and credit the authors.
corpus ashhart--tensorfold · AI, prompts and agents
Related corpora: haystack, adalflow, Hiburger/Wearstral, zendev-sh/goai
AI search and retrieval with XERJ · Case study: reference coding for agents
Selected work
ashhart/TensorFold
The corpus is the whole repository at the pinned commit, not only the files of the selected commit.
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.
Sign in with GitHub or Hugging Face to see more: every selected commit in full (commit date, every folder, licence review state, pin) and the pack builds of each corpus.
[](https://hub.xerj.org/contributors/cwschroeder)
Included with the author's permission (email, 2026-10-23), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.