ISNAD: adapting classical isnad–rijal chain-of-transmission verification into a claim-level trust layer for multi-agent LLM systems [R]

I'm the author. Sharing a preprint + code and looking for critique, especially on the parts I haven't validated yet.

Problem. In a multi-agent pipeline, one answer passes through a scraper, an extractor, several models, a synthesizer. Some links are reliable, some aren't, and when they fail they fail silently — you get a fluent, confident answer that's quietly wrong. Most current work verifies the agent (identity, permissions, access). Far less verifies the claim: whether what was actually said is true and independently corroborated.

Approach. There's a ~12-century-old methodology for exactly this failure mode. Early Islamic scholars, verifying transmitted statements, built a system where every claim carries its full chain of transmitters (isnād), each transmitter is graded on integrity and precision (rijāl), a chain is only as strong as its weakest link, independent chains raise confidence, and a flawless chain still doesn't excuse a flawed message (the content is critiqued separately). I adapt this into claim-level provenance for multi-agent AI: each claim carries a graded transmission chain, corroboration across independent chains is scored, and content is evaluated on its own axis.

On the evaluation. Some mechanisms are validated in the paper; others aren't yet, and I say exactly which and why. A trust framework that hides its own weaknesses is self-defeating, so the failure modes are written into the paper in detail rather than buried.

Paper: https://arxiv.org/abs/2607.24117
Code + eval: https://github.com/alizahidraja/isnad

Happy to be told where the analogy breaks or where the eval is thin — that's the feedback I want.