formal-logic-reasoner

Skill for formal logical reasoning and argument validation

509 stars

Best use case

formal-logic-reasoner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Skill for formal logical reasoning and argument validation

Teams using formal-logic-reasoner should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/formal-logic-reasoner/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/scientific-discovery/skills/formal-logic-reasoner/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/formal-logic-reasoner/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How formal-logic-reasoner Compares

Feature / Agentformal-logic-reasonerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Skill for formal logical reasoning and argument validation

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Formal Logic Reasoner Skill

## Purpose

Apply formal logic for argument validation, logical consistency checking, and deductive reasoning in scientific contexts.

## Capabilities

- Formalize arguments
- Check logical validity
- Identify fallacies
- Perform deductive reasoning
- Validate proof structures
- Generate logical conclusions

## Usage Guidelines

1. Parse argument structure
2. Formalize propositions
3. Apply inference rules
4. Check validity
5. Identify issues
6. Report conclusions

## Process Integration

Works within scientific discovery workflows for:
- Argument validation
- Theory consistency checking
- Logical analysis
- Proof verification

## Configuration

- Logic system selection
- Formalization rules
- Validation criteria
- Output formatting

## Output Artifacts

- Formalized arguments
- Validity assessments
- Fallacy reports
- Logical analyses

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