Who is this skill intended for?

It is specifically designed for business analysts and senior managers who need to extract core messages from dense, often noisy, non-fiction or corporate texts.

How does the 'denoising' process work?

Denoising identifies and removes 'corporate speak,' buzzwords, performative professionalism, and promotional rhetoric that lacks substantive operational detail.

Does this skill add new information or assumptions?

No, the skill guidelines strictly forbid adding new facts, making inferences, or modifying numbers and names to ensure the integrity of the original data.

Can it detect bias in reporting?

Yes, the 'Analyze' step explicitly detects logical errors, cognitive biases, hidden messages, and potential source biases from governments, consultants, or competitors.

What kind of output can I expect?

The output includes a one-sentence title of the key message, a structured bullet-point summary of core information, and up to three concise editor notes.

Journalist Editor

Name: Journalist Editor
Author: Shura1oplot

byShura1oplot

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Content Management

Refines and distills non-fiction business texts into high-signal summaries for analysts and executives.

About

The Journalist Editor skill transforms raw text into professional, noise-free intelligence by acting as a chief editor at a non-fiction publishing house. It systematically removes corporate buzzwords, identifies logical fallacies, and strips away promotional rhetoric to deliver concise, factual summaries. Specifically designed for senior managers and business analysts, it ensures that only data-driven insights and verifiable claims remain, while flagging uncertainties, conflicting reports, and potential source biases to facilitate faster, more accurate decision-making.

Key Features

Multi-stage text denoising to remove buzzwords and performative fluff
Structural decomposition into facts, methodology, and implications
Deep critical analysis for logical errors and cognitive biases
Claim distillation that removes non-falsifiable statements and superlatives
Data hygiene verification for metrics, timeframes, and baselines
1 GitHub stars

Use Cases

Summarizing dense corporate reports for executive briefings
Auditing marketing copy to separate factual claims from PR noise
Synthesizing competitor announcements into actionable business intelligence

About

Key Features

Multi-stage text denoising to remove buzzwords and performative fluff
Structural decomposition into facts, methodology, and implications
Deep critical analysis for logical errors and cognitive biases
Claim distillation that removes non-falsifiable statements and superlatives
Data hygiene verification for metrics, timeframes, and baselines
1 GitHub stars

Use Cases

Summarizing dense corporate reports for executive briefings
Auditing marketing copy to separate factual claims from PR noise
Synthesizing competitor announcements into actionable business intelligence