Audit Claude output across four passes and produce a corrected version with an error report.
npx skills add https://github.com/kategage/progressive-ai-skills --skill brown-mm
Please help me install this Agent Skill. Skill: brown-mm Source: https://github.com/kategage/progressive-ai-skills/tree/main/skills/brown-mm Command: npx skills add https://github.com/kategage/progressive-ai-skills --skill brown-mm
This skill helps users uncover and fix hidden errors in Claude's outputs by performing a disciplined, multi-pass audit that surfaces inconsistencies, factual errors, and overlooked details.
Drop the SKILL.md into your skills directory and invoke the audit when you spot an error to receive a corrected output with a transparent findings report.
High-intent search queries and answers about installing and using this skill.
To audit AI output for factual errors and internal consistency, run a four-pass review process that verifies facts, checks logical structure, and re-reads with fresh eyes to produce a corrected version and a transparent error report.
A multi-pass error detection workflow systematically scans generated content across four stages: fact verification, internal consistency checks, logical structure review, and a fresh-eyes re-read to surface and fix hidden inconsistencies.
Yes, a post-output audit skill applies universally across emails, code, documents, research, and plans, performing fact verification and logical structure checks to deliver a clean, validated output with an explicit accounting of found issues.
To fix overlooked details and inconsistencies in generated text, apply a disciplined multi-pass audit that enforces fact verification and internal consistency checks, replacing the flawed output with a corrected version and a transparent findings log.
The best way to perform quality assurance on AI-generated content is a four-pass audit workflow covering fact verification, internal consistency, logical structure, and fresh-eyes review, yielding a corrected document and an explicit error log.
You should invoke an error detection skill when you spot an error in Claude's output or explicitly need a thorough post-output audit, triggering a four-pass review that produces a corrected version and a transparent error report.
jackspaceConsult Gemini, Codex, and Fresh Claude for second opinions on critical decisions.
JaviMontanoGenerate a project communication plan with stakeholder matrices, cadences, channels, and templates.
LaZy-WolfVerify research drafts through citation validation, fact-checking, and content quality assessment.
cmg777Validate data science blog posts for correctness, display, and consistency.
