ubiquitous-language

ubiquitous-language is a skill for Claude Code from KaydenClark/LLM_Workbench. It costs 70 tokens per session (1,050 once invoked), scanned A, a copy of ubiquitous-language, MIT.

A glossary maker for domain-driven design, a software approach that models a business area using its own precise terms. It extracts important words from a conversation and saves a consistent vocabulary to a file.

In plain words
What is it for?
Use it to define domain terms, choose canonical names, document a domain model, and create or update a UBIQUITOUS_LANGUAGE.md glossary.
Why use it?
It exposes ambiguous words, synonyms, and overloaded terms before they cause misunderstandings in requirements or code.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to define domain terms, choose canonical names, document a domain model, and create or update a UBIQUITOUS_LANGUAGE.md glossary.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kaydenclark/llm_workbench/ubiquitous-language
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add KaydenClark/LLM_Workbench --skill ubiquitous-language
Clone the repo
git clone --depth 1 https://github.com/KaydenClark/LLM_Workbench

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ubiquitous-language

README.md
[![agentmods](https://agentmods.dev/badge/skills/kaydenclark/llm_workbench/ubiquitous-language/github.svg)](https://agentmods.dev/skills/kaydenclark/llm_workbench/ubiquitous-language)
Your own site
<a href="https://agentmods.dev/skills/kaydenclark/llm_workbench/ubiquitous-language"><img src="https://agentmods.dev/badge/skills/kaydenclark/llm_workbench/ubiquitous-language/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ubiquitous-language

Your own site · 80×15
<a href="https://agentmods.dev/skills/kaydenclark/llm_workbench/ubiquitous-language"><img src="https://agentmods.dev/badge/skills/kaydenclark/llm_workbench/ubiquitous-language.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.01050
Opus 5 $0.00035 $0.00525
Sonnet 5 $0.00014 $0.00210
Haiku 4.5 $0.00007 $0.00105

Measured 9d ago against content hash 2449e2345b96, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ubiquitous-language scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to ubiquitous-language — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills-pending/ubiquitous-language/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ubiquitous Language

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**.

Read the full file on GitHub · 94 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 94 lines · 70 tokens per session scan A 2449e2345b96

Subscribe to this mod's changes

ubiquitous-language is a skill published in the GitHub repository KaydenClark/LLM_Workbench (2 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 1,050 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ubiquitous-language, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens