Conor Bronsdon

Revise text to remove formulaic AI phrasing while keeping the writer’s voice, facts, intent, and structure. It targets justified changes, preserves protected passages, and reports editing limits and any unresolved issues.

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• Removing formulaic AI phrasing from a draft
• Polishing text while keeping the writer’s voice
• Preserving technical details during a rewrite

Review English prose for formulaic phrases and other patterns associated with AI writing, then make targeted edits while preserving meaning and voice. Choose findings only, a rewritten version, or direct edits to a prose file.

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• Checking an English draft before publication
• Reviewing flagged phrases without changing the text
• Editing a Markdown draft directly

Compare original and revised text to check whether protected content survived editing. It combines a bundled validator for structural checks with a separate meaning review, then reports errors, warnings, and specific repair targets.

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• Checking quotes and code after a rewrite
• Comparing links, numbers, and headings before and after editing
• Reviewing changes to meaning, conditions, and uncertainty

Edit a specified local file to remove justified AI writing patterns through focused changes. It preserves voice, facts, protected content, and document structure, then rereads edits and reports file changes and verification status.

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• Cleaning up formulaic phrasing in a local draft
• Editing only a specified section of a long document
• Preserving quotes and metadata while polishing prose

Coordinate AI-style writing reviews, voice-preserving rewrites, file edits, and before-and-after checks. Route each request to the appropriate related skill, carry context between stages, and report which checks ran and whether the original meaning was preserved.

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• Combine a writing audit, rewrite, and preservation check
• Route an explicit request to edit a named file
• Select a workflow when no editing mode is specified

Interpret AI-writing flags without treating them as proof of authorship. Separate tool results from editorial observations, consider plausible human explanations, and identify drafts, revision histories, or other process evidence needed for consequential academic, hiring, or publication decisions.

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• Understand what AI-writing flags actually establish
• Consider false positives in second-language or technical writing
• Review detector evidence for academic or hiring decisions

Review text for common AI writing patterns without changing it. When Node execution is available, a local detector supplies scores and matches; contextual review separates useful editorial findings from possible false positives.

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• Reviewing a draft for formulaic AI phrasing
• Checking technical prose with context in mind
• Scanning Markdown without scoring its metadata