Nicholas Seney
Nicholas Seney'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 @nseney1 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 Aegis-Guardrails corpus
nseney1/Aegis-Guardrails: Project rules for AI coding agents. An MCP server gives Claude Code, Codex CLI and Antigravity the rules for the files they are about to…
- Look up how Aegis-Guardrails implements ai-governance, developer-tools, python, with answers cited to file and line.
- Reuse a worked example: the commit “consolidate v4.3.1 parsers, git plumbing, verificatio…” (38 files · Python).
- Answer from Aegis-Guardrails's real Python source instead of memory (AI, prompts and agents).
- How does Aegis-Guardrails implement ai-governance?
- What does aegis_core do in Aegis-Guardrails?
Search the GitHub repository nseney1/Aegis-Guardrails with XERJ (https://hub.xerj.org/corpus/nseney1--aegis-guardrails). 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/nseney1/Aegis-Guardrails Aegis-Guardrails && git -C Aegis-Guardrails checkout 3b2423211020e69d9cb9a646ebfb3a720beb1473 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./Aegis-Guardrails --url http://127.0.0.1:9200 --prefix aegis-guardrails --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 nseney1--aegis-guardrails · AI, prompts and agents
Related corpora: agno, haystack, halilogia/GravityGuard, smaniches/semantic-scholar-mcp
AI search and retrieval with XERJ · Case study: reference coding for agents
Selected work
nseney1/Aegis-Guardrails
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/nseney1)
Included with the author's permission (email, 2026-10-17), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.