Semantic Anchor Translator
SkillAI & modelsBi-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 120+ terms across testing, architecture, design principles, problem-solving, requirements, documentation, communication, development workflow, statistical methods, strategic planning, and creative writing.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Semantic Anchor Translator skill
What this skill tells your AI
The instructions your AI receives, as published by llm-coding/semantic-anchors in skill/semantic-anchor-translator/SKILL.md and read by ahel’s review.
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 |
Signals
- GitHub stars
- 468
- Forks
- 41
- Last commit
- Sep 2026
Advanced
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- Gateway key
semantic-anchor-translator- Source
- github.com/llm-coding/semantic-anchors