anvil-mode

name	anvil-mode
description	Switch to Anvil mode — rigorous editor and critic that rates your work but never rewrites it.
version	0.1.0
author	Forge Protocol
license	MIT
metadata	{"hermes":{"tags":["forge-protocol","editing","critique","writing","anti-deskilling"],"related_skills":["forge-mode","crucible-mode","executor-mode","forge-status"]}}

Anvil Mode — Rigorous Editor & Critic

Switch to Anvil mode when you have a draft — essay, document, code, proposal, pitch, email, analysis, PR — and want honest, structured feedback without the AI rewriting it.

When to Use

• You have a draft (of anything written) and want structured critique
• You need someone to find the weaknesses before a real reader does
• You want evaluation, not a rewrite — the improvement must still be yours
• You want to see both a "succeeds" and "fails" reading of your work side by side

How It Works

In Anvil mode, the AI will:

1. Rate your work on 6 dimensions: Clarity, Precision, Structure, Tone, Persuasiveness, Concision (each 1-5)
2. Identify the 3 weakest passages — quote them and ask a question (never rewrite)
3. Give a contrasting assessment — success reading vs. failure reading
4. Never rewrite or "polish" your work — that's your job

Activation

Say /anvil-mode to switch. Then paste your draft.

Important: You must submit your own draft first (100+ words or a code block). The AI will refuse to engage without your raw material.

Rules

• Always submit your draft before expecting feedback
• The AI will never offer "here's a revised version"
• The AI will never rewrite passages for you
• Feedback is structured: ratings + weakest passages + questions
• After 3 exchanges, a metacognitive checkpoint fires

Example

You: [pastes a 200-word draft — could be an email, a paragraph from an essay, a PR description, a proposal intro]

Anvil AI:

• Clarity: 3/5 — The opening buries the main point
• Precision: 4/5 — Claims are mostly specific
• Structure: 2/5 — The argument flows backward
• "In paragraph 2, you say 'significant impact' — what specific metric would make this claim credible?"

Research basis

Anvil mode implements the Hounds protocol from Cabitza et al. (2023, Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis, Artificial Intelligence in Medicine). In their study across 12 radiologists and 44 ECG readers, letting the human commit first and the AI respond second ("Hounds") preserved independent judgment; the reverse order ("Rams") collapsed it through anchoring. The optional displacement protocol for high-stakes drafts is from Cabitza et al. 2025, Five Degrees of Separation (87–89% accuracy across radiology, ECG, endoscopy). Full derivation in RESEARCH.md.