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- Rigorous Reasoning
rigorous-reasoning_skill
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2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill toilahuongg/shopify-agents-kit --skill rigorous-reasoning- SKILL.md7.8 KB
Overview
This skill provides a rigorous reasoning framework combining philosophical methods and scientific practices to analyze, evaluate, and construct arguments. It is designed for use in debates, proofs, critique, and complex problem solving where clear inference, fallacy detection, and evidential standards matter. The goal is to produce transparent, reproducible judgments and stronger arguments.
How this skill works
The skill reconstructs raw arguments into premises, inference rules, and conclusions, then evaluates each premise for truth, relevance, and sufficiency. It checks inference validity against formal rules (e.g., modus ponens, syllogism), flags formal and informal fallacies, and applies the scientific claim-evaluation cycle (hypothesis, prediction, testing, conclusion). It also uses tools like steel-manning, reductio ad absurdum, and Occam's Razor to refine and stress-test positions.
When to use it
- Evaluating the logical structure of an essay, speech, or policy claim
- Testing the validity of proofs or formal arguments
- Detecting and explaining logical fallacies in debates or media
- Designing falsifiable hypotheses and evidence-based tests
- Constructing well-supported positions for academic or technical writing
Best practices
- Start by reconstructing the argument into explicit premises and the stated conclusion
- Apply the principle of charity and steel-man the strongest opposing interpretation first
- Separate empirical claims (require evidence) from conceptual claims (require definition)
- Use the evidence hierarchy and ask what would falsify the claim
- Document hidden premises and evaluate their plausibility before accepting conclusions
Example use cases
- Turn a persuasive op-ed into a numbered premise-inference-conclusion form and identify weak links
- Assess whether a scientific claim is falsifiable and recommend tests or data to collect
- Analyze a debate transcript to locate ad hominem, straw man, or false dichotomy fallacies
- Formalize a conjecture, list assumptions, and outline a reductio ad absurdum or counterexample strategy
- Compare competing explanations and apply Occam's Razor to select the simplest viable hypothesis
FAQ
Yes. It adapts the same reconstruction-evaluate-test workflow: for informal arguments it emphasizes evidence and fallacy checks; for formal proofs it focuses on inference rules and validity.
How does it treat uncertain or probabilistic claims?
It asks for probabilistic evidence, assesses sample size and representativeness, and reports confidence levels rather than binary truth when claims rest on statistical or inductive support.