From 1c6124b9d51e7bff7dbbb5185c347379cec861a0 Mon Sep 17 00:00:00 2001
From: debpalash <4178343+debpalash@users.noreply.github.com>
Date: Thu, 16 Jul 2026 21:31:42 +0530
Subject: [PATCH] =?UTF-8?q?docs(contributing):=20AI-agent=20workflow=20tip?=
 =?UTF-8?q?=20=E2=80=94=20persistent=20memory=20(memxt)=20+=20the=20repo?=
 =?UTF-8?q?=20agent=20skill?=
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Agent-built contributions are common; re-explaining a codebase this size
every session wastes context and tokens. Point contributors at a local
MCP memory layer (memxt, by the maintainer — disclosed) and the repo's
skills package so agents start with the hard rules loaded.
---
 CONTRIBUTING.md | 15 +++++++++++++++
 1 file changed, 15 insertions(+)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index e9e491b3..83868b42 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -256,6 +256,21 @@ what's right, push back (in a reply) on what's wrong.
 (`fix(dub): …`, `feat(setup): …`) and link the issue (`Closes #N` / `Refs #N`)
 in the title or body.
 
+### Contributing with AI agents
+
+Plenty of contributions here are built with Claude Code, Cursor, and similar
+agents — welcome, with the same quality bar as hand-written PRs (real bug,
+correct fix, regression test; see the quality gates below).
+
+One practical tip: this codebase is large, and re-explaining it to your agent
+every session burns context and tokens fast. A persistent memory layer fixes
+that — the agent recalls the architecture, conventions, and your past findings
+instead of re-reading the tree each time. [**memxt**](https://github.com/debpalash/memxt)
+(100% local, MCP-based, built by this project's maintainer) exists for exactly
+this; any MCP memory server works. Pair it with the repo's agent skill —
+`npx skills add debpalash/omnivoice-studio` — so your agent knows the project's
+hard rules from the first prompt.
+
 ## Quality gates your PR must pass
 
 - **Cross-platform parity (hard rule):** anything that ships in default mode