todero-talk-like-a-colleague

Applies plain-language communication rules for direct, cost-based answers in agent responses.

Updated Mar 26, 2026
One-click install
npx skills add https://github.com/nabitllc/todero --skill todero-talk-like-a-colleague-nabitllc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: todero-talk-like-a-colleague
Source: https://github.com/nabitllc/todero/tree/main/skills/todero-talk-like-a-colleague
Command: npx skills add https://github.com/nabitllc/todero --skill todero-talk-like-a-colleague-nabitllc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI agents often bury answers under preamble, narrate their own process, and present choices in technical jargon that non-technical users cannot act on. This Skill enforces a colleague-like communication style so every response leads with the answer and describes options by what they cost. ## Core Features & Use Cases - Answer-First Responses: Requires the conclusion or recommendation in the first sentence, with no preamble, restating the question, or narration of the work performed. - Cost-Based Option Framing: Presents choices by what they cost in money or time and what breaks later, never by the underlying machinery. - Jargon Control: Defines any technical term the first time it appears, or makes the decision autonomously and reports it in one sentence when the question cannot be phrased plainly. - Use Case: A non-technical founder asks their AI operations team whether to change a deployment setup. Instead of a jargon-heavy explanation, the agent replies: doing it by hand takes two minutes each time; setting it up once takes an afternoon and never asks again. ## Quick Start Apply the talk-like-a-colleague rules so every agent reply leads with the answer and describes options by cost rather than mechanism.

Frequently Asked Questions about todero-talk-like-a-colleague

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

FAQPage Schema
How do I make AI agent responses more direct and less verbose?

Apply answer-first rules: put the conclusion in the first sentence, remove preamble and restated questions, and ban narration of the work process. Match response length to the stakes, keeping routine answers as short as correctness allows.

How should AI agents present options to non-technical users?

Describe each option by what it costs in money or time, what breaks later, and what stays quiet, never by the machinery involved. For example, say a manual approach takes two minutes each time while a one-time setup takes an afternoon.

What should an AI agent do when a question cannot be phrased plainly?

Make the decision itself and report it in one sentence with the reasoning. A decision the user cannot parse is a decision that stalls, so the agent states the call and the practical reason behind it.

Does this communication style work with any AI agent or task type?

Yes, the metadata marks it for all task kinds with priority 1, meaning it applies as a general tone layer across agent work. It governs how results are communicated, not what work is performed.

When should an agent not shorten its response?

When the stakes are high. The rules state a hard truth gets as long as it takes, while a routine answer stays as short as correctness allows. Brevity never means dropping facts, only dropping words.