Hone MCP server

Hone

Keep your edge.

AI made producing work cheap. Hone measures the thing that's now scarce: whether the human actually understands the work they shipped with AI.

Every AI eval scores the model. Hone scores you — your AI-Q.

What it feels like · Quickstart · AI-Q · Why · Whitepaper

The 30-second version

Every AI eval tool answers one question: was the model's output good? (accuracy, hallucination, toxicity, latency, cost.)

None of them answer the question that actually decides whether AI-assisted work is safe to ship: does the human who produced it understand it well enough to defend it?

Hone is an open toolkit for measuring exactly that. Give it a piece of AI-assisted work; it interviews the human — a few sharp questions, one at a time, the way a good mentor would — then returns their AI-Q: a score over the three Ds of working with AI. Discernment (can you tell when the AI is wrong? — six auditable dimensions, the spine of the score), Delegation (did you brief it, choose the task, and steer it well?), and Design (are you re-architecting how you work? — read over time, never faked from one review).

It's bring-your-own-model (any LLM), Apache-2.0, and drops into a coding agent, a CI pipeline, or your own app in minutes. The methodology is an open spec — the AI-Q — the open standard — so the score means the same thing everywhere it's computed.

What a review feels like

You:  Run hone on the pricing analysis we just built.

Sol:  Happy to take a look. This is a strategy memo recommending a Pro-tier
      price increase — real money riding on it, so I'll ask five questions.
      Just between us, and "I don't know" is a perfectly useful answer.

      First: walk me through the recommendation in your own words —
      why $49, and not $39 or $59?

      ...three more, one at a time — including: what did you give the
      AI to work with, and what did you have to correct in its first
      answer? ...

      Last one: before I show you anything — honestly, how confident
      are you in this work, 0 to 100?

You:  85.

Sol:  Here's my read.

      Pro-tier pricing recommendation · AI-Q 58 — Mostly owns it
      (discernment 57 · delegation 60)
      You can explain the mechanism, but you took the churn projection
      on faith — and that's the load-bearing number.

      Work on this first: the 4% churn assumption came straight from the
      AI with no source. If churn runs 8%, the revenue case inverts.

      [ what a rigorous review surfaced vs. what you caught ]
      [ before-you-ship checklist · the toughest objection you'll face ]
      [ w

No grades for the work. No "AI detector." A measure of your grip on it — and coaching to close the gap.

Quickstart

In your coding agent (the best way) — review work where it lives

When an agent built the thing — a repo, an analysis, a doc set — don't paste it anywhere. Hone runs inside the agent, which already has the work loaded:

Claude Desktop — one click: download hone.mcpb from the latest release and open it (Settings → Extensions). No config files, no terminal.

Claude Code — add the MCP server (protocol + deterministic scoring):

Shortened. The full README is on GitHub.