
LogicGuard
Build reusable logic chains for serious writing
4 followers
Build reusable logic chains for serious writing
4 followers
LogicGuard is an AI-facing logic-chain skill layer for research, reports, and serious writing. Agents use its subskills to build reusable logic model libraries from papers, books, reports, URLs, and drafts; map claims, evidence, warrants, limits, and rebuttals; audit weak links; and synthesize new paper outlines, technical reports, deck storylines, review responses, or cautious rewrites from existing models without inventing support.




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Hey Product Hunt,
I built LogicGuard because AI agents are getting good at drafting, but they still need a durable way to build and reuse the logic behind serious writing.
LogicGuard is an AI-facing logic-chain skill layer. It is not just a checker. Its subskills help an agent:
- preserve papers, books, reports, URLs, pasted text, and drafts into a source logic library;
- turn sources and drafts into reusable logic models: claims, evidence, warrants, assumptions, rebuttals, scope, and limitations;
- link project claims back to source nodes and anchored branches;
- audit whether the current logic chain is strong enough;
- synthesize new artifacts from existing models: paper outlines, technical reports, deck storylines, review responses, README positioning, and cautious rewrites.
The workflow I care about is:
find or collect material -> model the logic -> build a reusable model library -> select and reuse existing nodes -> synthesize a new paper, report, or storyline -> check where support is missing before writing too confidently.
So the core product is the skill system and model library that gives AI a memory of reasoning structure. The CLI, viewer, and source-library UI are support surfaces for preserving, inspecting, and moving those models.
It is especially useful for researchers, technical writers, and AI-agent users who work with many sources and need to produce papers, reports, briefs, or rebuttals without losing the logic chain.
I would love feedback on:
1. Is the model-library + synthesis story clear in the first minute?
2. Which output should the demo emphasize first: paper outline, technical report, deck storyline, review response, or AI-answer repair?
3. What kind of source-library UI would make reuse easiest?
@new_user___1302026a824c3017e32a6f7
I like that LogicGuard focuses on reusable claims, evidence, warrants, assumptions, limits, and rebuttals... especially for serious writing where inventing support is dangerous.
сurious, how you imagine people using this first: research papers, technical reports, investor decks, or long-form strategic writing?