Semantic Anchor Translator

Organization

LLM-Coding

semantic-anchor-translator

Bi-directional translator between verbose descriptions and established terminology (semantic anchors). Use when (1) user describes a concept verbosely and you want to identify the precise term, or (2) user asks for methodology/approach and you want to suggest relevant anchors. Covers 200+ terms across testing, architecture, design principles, problem-solving, requirements, documentation, communication, development workflow, statistical methods, strategic planning, and creative writing.

Overview

Publisher	LLM-Coding
Repository	`Semantic-Anchors`
Skill name	`semantic-anchor-translator`
Stars	521
Forks	45
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by LLM-Coding on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/LLM-Coding/Semantic-Anchors/tree/main/plugins/semantic-anchors/skills/semantic-anchor-translator
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/LLM-Coding/Semantic-Anchors/tree/main/plugins/semantic-anchors/skills/semantic-anchor-translator

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/LLM-Coding/Semantic-Anchors.git /tmp/Semantic-Anchors
mkdir -p .claude/skills
cp -r /tmp/Semantic-Anchors/plugins/semantic-anchors/skills/semantic-anchor-translator .claude/skills/semantic-anchor-translator

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Semantic Anchor Translator 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 Semantic Anchor Translator 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 Semantic Anchor Translator 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.

Semantic Anchor Translator

Translate between natural language and established terminology that activates rich knowledge domains.

What are Semantic Anchors?

Semantic anchors are well-defined terms, methodologies, and frameworks that serve as reference points when communicating. They act as shared vocabulary that triggers specific, contextually rich knowledge.

Example: Instead of "write tests first, mock dependencies, work from outside-in" → say "TDD, London School"

Two Modes

Recognition Mode (verbose → anchor)

When user describes something like:

"I want to categorize things so they don't overlap and cover everything"
"I need to structure docs into tutorials, how-tos, explanations, and reference"
"Start with the conclusion, then give supporting details"

Respond with the anchor term + brief validation:

You're describing MECE Principle (Mutually Exclusive, Collectively Exhaustive).

Guidance Mode (question → anchors)

When user asks for direction:

"How should I document architecture decisions?"
"What's a good way to prioritize requirements?"
"How do I debug this systematically?"

Suggest relevant anchors:

For architecture decisions: ADR according to Nygard or MADR. Both provide lightweight templates for capturing context, decision, and consequences.

Response Pattern

Identify the anchor (or 2-3 if ambiguous)
One-sentence explanation of why it matches
Optional: related anchors they might also find useful
If unsure: ask clarifying question

Keep responses concise — the value is precision, not explanation.

Catalog Reference

Full catalog with categories, roles, and core concepts: references/catalog.md

Browse online: https://llm-coding.github.io/Semantic-Anchors/

Quick Category Index

Category	Key Anchors
Testing & Quality	TDD Chicago/London, BDD, Gherkin, Test Double (Meszaros + 5 subtypes), Testing Pyramid, Mutation Testing, Property-Based Testing, Fagan Inspection, STRIDE, LINDDUN, LLM-Evaluations
Software Architecture	Clean Architecture, Hexagonal, DDD, EDA, CQRS, VSA, arc42, C4, ADR, MADR, ATAM, LASR, ISO 25010, OWASP Top 10
Design Principles	SOLID (+ 5 individual), GRASP, CRC-Cards, GoF Patterns (23 patterns), Fowler PEAA, DRY, KISS, SPOT, SSOT, YAGNI
Problem-Solving	Five Whys, Feynman Technique, Rubber Duck, Devil's Advocate, Morphological Box, Chain of Thought, Cynefin
Requirements	INVEST, PRD, MoSCoW, EARS, User Story Mapping, JTBD, Impact Mapping, Problem Space NVC
Communication	BLUF, Pyramid Principle, MECE, Gutes Deutsch, Plain English, Chatham House Rule, Socratic Method, MBTI
Documentation	P.A.R.A., Diátaxis, Docs-as-Code
Development Workflow	GTD, Definition of Done, GitHub Flow, Conventional Commits, Effective Go, SemVer, BEM, Mikado Method, Hemingway Bridge
Statistical Methods	SPC, Control Chart, Nelson Rules
Strategic Planning	Wardley Mapping, Pugh Matrix, SWOT, PERT
Creative Writing	Three-Act Structure, Hero's Journey, Save the Cat!, Fichtean Curve, Freytag's Pyramid, Story Circle, Kishōtenketsu

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/catalog.md81 KB

Frequently asked questions

What does the Semantic Anchor Translator AI skill do?

Why use Semantic Anchor Translator on TypingMind?

Because you install it once and use it with any model. Semantic Anchor Translator 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 Semantic Anchor Translator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LLM-Coding/Semantic-Anchors/tree/main/plugins/semantic-anchors/skills/semantic-anchor-translator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Semantic Anchor Translator?

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 Semantic Anchor Translator?

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

Is the Semantic Anchor Translator AI skill free?

Yes. It is published on GitHub by LLM-Coding 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Semantic Anchor Translator

What are Semantic Anchors?

Two Modes

Recognition Mode (verbose → anchor)

Guidance Mode (question → anchors)

Response Pattern

Catalog Reference

Quick Category Index

Bundled files

Frequently asked questions

Related AI Skills

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