LynkMesh is a deterministic MeshContext evidence protocol for AI coding agents.
It is not just a repository indexer.
Repository indexing helps AI find code. MeshContext helps AI reason from evidence.
LynkMesh turns codebases into graph-backed, inspectable context artifacts that AI-assisted engineering workflows can use before reasoning about architecture, impact, and code changes.
The current open-core release focuses on:
- deterministic graph evidence
- MeshContext reports
- AI Context Packs
- token benchmark artifacts
- structural validation
- public-safe before/after evidence packs
LynkMesh separates deterministic codebase facts from AI interpretation.
The evidence layer is generated by LynkMesh. Interpretation, explanation, and final judgment remain above that layer and should be reviewed by humans.
LynkMesh is not positioned as:
- a general code search engine
- a replacement for IDE indexing
- a replacement for AI coding assistants
- a claim that an AI model became smarter
- benchmark proof
- runtime truth
- production-ready impact certainty
The public evidence pack is an early validation baseline. It shows fixture-level evidence for how deterministic MeshContext artifacts can support AI-assisted code understanding workflows.
Many tools help retrieve code, index repositories, search symbols, or summarize nearby files.
LynkMesh focuses on a different layer: deterministic MeshContext evidence.
That means LynkMesh is designed to provide:
- graph-backed facts instead of raw snippets alone
- compact AI-ready context instead of repeated full-repo scanning
- guardrails that distinguish evidence from inference
- artifacts that can be reviewed, committed, compared, and tested
- privacy-aware context packaging without exposing raw private source code by default
AI coding agents can be useful, but they often reason from incomplete or noisy context.
LynkMesh gives the agent a structured map before asking it to reason.
The goal is not to replace the model. The goal is to improve the evidence layer the model can inspect.
LynkMesh is currently an open-core research preview.
The public release is suitable for early validation, technical review, and feedback.
It should not be treated as production-ready benchmark evidence.