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communication-pragmatics

Analyze engineering text for pragmatic meaning and implied commitments.

2|Updated Apr 30, 2026
Search Tags:#code review#documentation#technical writing#communication#prompts#error messages#pragmatics
One-click install
npx skills add https://github.com/NlightNFotis/skills --skill communication-pragmatics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: communication-pragmatics
Source: https://github.com/NlightNFotis/skills/tree/main/communication-pragmatics
Command: npx skills add https://github.com/NlightNFotis/skills --skill communication-pragmatics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you prevent communication failures caused by wording that is technically correct but pragmatically misleading. It improves how readers interpret and respond to engineering text such as error messages, commit messages, PR descriptions, log lines, prompts, and documentation.

Core Features & Use Cases

  • Pragmatic analysis of engineering text: Evaluates wording using Grice's maxims, speech act theory, implicature, and commitment analysis.
  • Action-oriented rewrites: Refines text so readers take the intended next step without confusion, panic, or false reassurance.
  • Interpersonal communication support: Helps calibrate tone and directness in PR feedback, design comments, and async team discussions without sacrificing clarity.
  • Use cases: Reviewing whether a warning message sounds optional when action is required, rewriting a vague commit message, making log lines clearer for on-call responders, or tightening prompts that accidentally permit unwanted behavior.

Quick Start

Ask the communication-pragmatics skill to analyze a draft error message, commit message, PR description, log line, or prompt and rewrite it so the audience draws the intended inference and takes the right action.

Frequently Asked Questions about communication-pragmatics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I rewrite error messages and warnings so users take the intended action?▼

To rewrite error messages and warnings for action, you analyze pragmatic meaning, intended action, and likely reader inferences to calibrate force and prevent false reassurance. This ensures the audience draws the correct conclusion and responds appropriately without confusion or panic.

What is pragmatic analysis of engineering text and when do I need it?▼

Pragmatic analysis of engineering text evaluates wording using Grice's maxims, speech act theory, implicature, and commitment analysis. You need it when technically correct wording risks misleading readers, causing misinterpretation in documentation, log lines, or prompts.

How do I make commit messages and PR descriptions clearer for reviewers?▼

To make commit messages and PR descriptions clearer, apply audience-aware rewriting to detect implicatures and implied commitments. This refines the text so reviewers understand the exact changes and required feedback without guessing the author's intent.

Best way to calibrate tone in code review comments without sacrificing clarity?▼

The best way to calibrate tone in code review comments is applying force calibration and speech act classification to interpersonal text. This adjusts directness in PR feedback and async discussions while maintaining clear, actionable communication.

How do I tighten prompts to prevent unwanted behavior in AI outputs?▼

To tighten prompts and prevent unwanted behavior, analyze the text for implicatures that accidentally permit unintended actions. Audience-aware rewriting refines the prompt boundaries so the system draws only the intended inferences.

How do I improve log lines for on-call responders during incidents?▼

To improve log lines for on-call responders, analyze the pragmatic meaning and likely reader inferences of the text. Rewriting with force calibration ensures responders immediately understand the severity and take the correct troubleshooting steps.

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