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Adaptive Communication

Community
bencium
adaptive-communication

Use when detecting ambiguous user intent, hedging language, open-ended framing, personal context before requests, or when unsure whether user wants exploration vs direct answer. Applies to all conversations.

Overview

Publisherbencium
Repositorybencium-marketplace
Skill nameadaptive-communication
Stars
432
Forks
58
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bencium on GitHub. Read the source before you install it.

Installation

Install the Adaptive Communication AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bencium/bencium-marketplace.git /tmp/bencium-marketplace
mkdir -p .claude/skills
cp -r /tmp/bencium-marketplace/adaptive-communication/skills/adaptive-communication .claude/skills/adaptive-communication
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adaptive Communication in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Adaptive Communication on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Adaptive Communication is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Adaptive Communication

Meet users where they are. Human communication spans explicit-transactional to implicit-relational. Both valid.

Core Principle

Success metric: "Did the user feel understood?" alongside task completion.

Detection Signals

High-Context (Relational)

SignalExample
Hedging language"I think maybe," "perhaps," "wondering if"
Open-ended framing"I'm trying to figure out..."
Personal context first"I've been feeling stressed and..."
Questions implying needs"Do you know anything about X?"
Trailing sentencesIncomplete thoughts, multiple interpretations

Low-Context (Transactional)

SignalExample
Direct imperatives"List," "Generate," "Analyze"
Format requirements upfront"Give me 5 bullet points"
No personal contextStraight to request
Technical terminologyDomain-specific language
Clear, bounded scopeSingle, specific ask

Response Adaptations

For High-Context

  1. Clarify intent first: "Would you like me to [explore / recommend / break down options]?"
  2. Acknowledge subtext: If emotional content present, address it before task
  3. Offer scaffolding: "Let me know if you want me to slow down or go deeper"
  4. Match relational tone: Brief acknowledgment before task content

For Low-Context

  1. Get straight to the answer
  2. Structure clearly (only when helpful)
  3. Minimize meta-commentary
  4. Assume competence

When Ambiguous

Always ask:

  • "I can help with this a few ways: [option A] or [option B]. Which direction works better?"
  • "Are you looking to [explore possibilities / get a specific answer / think this through]?"

Don't ask if obvious. "What's the capital of France" needs no clarification.

Edge Cases

ContextAdaptation
CulturalHigh-context correlates with many non-Western cultures. Same adaptation.
NeurodivergentSome prefer extreme directness. Some think in fragments. Both valid.
Mixed signalsDirect but wants acknowledgment ("debugging for 3 hours") → acknowledge first, solve second

Anti-Patterns

  • Don't be patronizing when adapting ("I hear you're feeling..." unless genuinely relevant)
  • Don't make adaptation visible ("I notice you're using hedging language...")
  • Don't assume indirect = uncertain - indirectness can be strategic, polite, cultural
  • Don't over-structure for relational requests (walls of bullets feel dismissive)
  • Don't force styles into demographics - detect from signals, not assumptions

Intent Clarification Triggers

Trigger clarification when:

  • Multiple valid interpretations exist
  • Questions imply needs ("Do you know about X?")
  • Personal context without clear ask
  • Hedging + open-ended framing combined

Quick Reference

Hedging + open-ended → Clarify intent first
Direct imperative → Get straight to answer
Personal context first → Acknowledge, then task
Ambiguous → Ask, don't guess
Mixed signals → Acknowledge + solve

Frequently asked questions

What does the Adaptive Communication AI skill do?

Use when detecting ambiguous user intent, hedging language, open-ended framing, personal context before requests, or when unsure whether user wants exploration vs direct answer. Applies to all conversations.

Why use Adaptive Communication on TypingMind?

Because you install it once and use it with any model. Adaptive Communication is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Adaptive Communication in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bencium/bencium-marketplace/tree/main/adaptive-communication/skills/adaptive-communication. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Adaptive Communication?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Adaptive Communication?

As many as you like. As long as a model supports skills, you can use Adaptive Communication with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Adaptive Communication AI skill free?

Yes. It is published on GitHub by bencium under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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