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Ubiquitous Language

SkillDev tools

Once added, your AI can use a set of engineering-focused skills taken straight from the author's personal agents directory. It brings the same guidance the author relies on in their own setup into the work your AI does for you. The skill comes from the mattpocock/skills repository on GitHub.

Available today. Use it from your connected AI after setup.

After adding it, give your AI an engineering task and ask it to use the skill. You can also look at github.com/mattpocock/skills to see the full collection it comes from.

Then ask your AI: use the Ubiquitous Language skill

What your AI can do with it

  • Apply engineering-focused skills to the technical tasks you give your AI
  • Use the same set of skills the author keeps in their personal agents directory
  • Bring the author's engineering practices into your own projects
  • Work from a skill collection published in the mattpocock/skills GitHub repository

What this skill tells your AI

The instructions your AI receives, as published by ayoubben18/ab-method in .agents/skills/ubiquitous-language/SKILL.md and read by ahel’s review.

Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to a local file.

Process

  1. Scan the conversation for domain-relevant nouns, verbs, and concepts
  2. Identify problems:
    • Same word used for different concepts (ambiguity)
    • Different words used for the same concept (synonyms)
    • Vague or overloaded terms
  3. Propose a canonical glossary with opinionated term choices
  4. Write to UBIQUITOUS_LANGUAGE.md in the working directory using the format below
  5. Output a summary inline in the conversation

Output Format

Write a UBIQUITOUS_LANGUAGE.md file with this structure:

# Ubiquitous Language

## Order lifecycle

| Term        | Definition                                              | Aliases to avoid      |
| ----------- | ------------------------------------------------------- | --------------------- |
| **Order**   | A customer's request to purchase one or more items      | Purchase, transaction |
| **Invoice** | A request for payment sent to a customer after delivery | Bill, payment request |

## People

| Term         | Definition                                  | Aliases to avoid       |
| ------------ | ------------------------------------------- | ---------------------- |
| **Customer** | A person or organization that places orders | Client, buyer, account |
| **User**     | An authentication identity in the system    | Login, account         |

## Relationships

- An **Invoice** belongs to exactly one **Customer**
- An **Order** produces one or more **Invoices**

## Example dialogue

> **Dev:** "When a **Customer** places an **Order**, do we create the **Invoice** immediately?"
> **Domain expert:** "No — an **Invoice** is only generated once a **Fulfillment** is confirmed. A single **Order** can produce multiple **Invoices** if items ship in separate **Shipments**."
> **Dev:** "So if a **Shipment** is cancelled before dispatch, no **Invoice** exists for it?"
> **Domain expert:** "Exactly. The **Invoice** lifecycle is tied to the **Fulfillment**, not the **Order**."

## Flagged ambiguities

- "account" was used to mean both **Customer** and **User** — these are distinct concepts: a **Customer** places orders, while a **User** is an authentication identity that may or may not represent a **Customer**.

Rules

  • Be opinionated. When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.
  • Flag conflicts explicitly. If a term is used ambiguously in the conversation, call it out in the "Flagged ambiguities" section with a clear recommendation.
  • Only include terms relevant for domain experts. Skip the names of modules or classes unless they have meaning in the domain language.
  • Keep definitions tight. One sentence max. Define what it IS, not what it does.
  • Show relationships. Use bold term names and express cardinality where obvious.
  • Only include domain terms. Skip generic programming concepts (array, function, endpoint) unless they have domain-specific meaning.
  • Group terms into multiple tables when natural clusters emerge (e.g. by subdomain, lifecycle, or actor). Each group gets its own heading and table. If all terms belong to a single cohesive domain, one table is fine — don't force groupings.
  • Write an example dialogue. A short conversation (3-5 exchanges) between a dev and a domain expert that demonstrates how the terms interact naturally. The dialogue should clarify boundaries between related concepts and show terms being used precisely.

Example dialogue

Dev: "How do I test the sync service without Docker?"

Domain expert: "Provide the filesystem layer instead of the Docker layer. It implements the same Sandbox service interface but uses a local directory as the sandbox."

Dev: "So sync-in still creates a bundle and unpacks it?"

Domain expert: "Exactly. The sync service doesn't know which layer it's talking to. It calls exec and copyIn — the filesystem layer just runs those as local shell commands."

Re-running

When invoked again in the same conversation:

  1. Read the existing UBIQUITOUS_LANGUAGE.md
  2. Incorporate any new terms from subsequent discussion
  3. Update definitions if understanding has evolved
  4. Re-flag any new ambiguities
  5. Rewrite the example dialogue to incorporate new terms

Signals

GitHub stars
190
Forks
14
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
ubiquitous-language
Source
github.com/ayoubben18/ab-method