Siddarth
Siddarth'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 @Siddarthb07 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 bumblebee-cec corpus
Siddarthb07/bumblebee-cec: Transformer-free closed-corpus correlator. Ask, cite, or refuse from a frozen pack. Not a chatbot LLM
- Look up how bumblebee-cec implements abstention, machine-learning, nlp, with answers cited to file and line.
- Reuse a worked example: the commit “Publish the dim-640 scoreboard and Hearth path.” (29 files · Python).
- Answer from bumblebee-cec's real Python source instead of memory (AI, prompts and agents).
- Where does bumblebee-cec handle “Publish the dim-640 scoreboard and Hearth path.”?
- How does bumblebee-cec implement abstention?
- What does src/bumblebee do in bumblebee-cec?
Search the GitHub repository Siddarthb07/bumblebee-cec with XERJ (https://hub.xerj.org/corpus/siddarthb07--bumblebee-cec). 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/Siddarthb07/bumblebee-cec bumblebee-cec && git -C bumblebee-cec checkout 6471edb54b17600f27a63ce9c79d85b78e61478a 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./bumblebee-cec --url http://127.0.0.1:9200 --prefix bumblebee-cec --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 siddarthb07--bumblebee-cec · AI, prompts and agents
Related corpora: opennyai-legal-nlp, fastrag, RizgarOzan/turkish-rag-eval, tarunagarwal1981/wobbly
AI search and retrieval with XERJ · Case study: reference coding for agents
Selected work
Siddarthb07/bumblebee-cec
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/Siddarthb07)
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.