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Agent skill

Define Language

by danielvm-git in danielvm-git/bigpowers

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms.

MITAuto-check passedDevelopment

Install Define Language

skills CLI
$ npx skills add danielvm-git/bigpowers --skill define-language -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install danielvm-git/bigpowers define-language --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/danielvm-git/bigpowers.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/define-language .claude/skills/define-language && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
define-language
GitHub stars
257
Token cost
~994 tokens
SKILL.md length
312 words
Files
1
Skills in repo
39
Repo updated
First seen
Licence
MIT

At a glance

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms.

  • Works in 5 steps: Scan the conversation for… → Identify problems → Propose a canonical glossary with… → …
  • User wants to define domain terms
  • SKILL.md covers Process, Output Format, Rules and Re-running
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Define Language is an agent skill from danielvm-git/bigpowers. Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to specs/UBIQUITOUSLANGUAGELATEST.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Domain-driven design. The repository describes itself as: Agent skills synthesizing years of software engineering discipline into a prescriptive methodology for solo developers. The licence is MIT.

When your agent uses it

  • User wants to define domain terms
  • Build a glossary
  • Harden terminology
  • Create a ubiquitous language

Example prompts

  • “domain model”
  • “/define-language”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Scan the conversation for domain-relevant nouns, verbs, and concepts
  2. Identify problems
  3. Propose a canonical glossary with opinionated term choices
  4. Write to specs/UBIQUITOUS_LANGUAGE_LATEST.md in the working directory using the format below
  5. Output a summary inline in the conversation

What it can do on your machine

Read from SKILL.md and the folder at commit 812d57a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Define Language loads about 994 tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 312 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~86
When it runs · the whole SKILL.md, loaded when a task matches
~994

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from danielvm-git/bigpowers at commit 812d57a, republished under its MIT licence (© danielvm-git). 312 words, ~994 tokens.

Download SKILL.mdSave it as .claude/skills/define-language/SKILL.md (or your agent's skills folder).
name
define-language
description
Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to specs/UBIQUITOUS_LANGUAGE_LATEST.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
model
sonnet
effort
standard

Define Language

Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to specs/UBIQUITOUS_LANGUAGE_LATEST.md.

Distinct from model-domain and deepen-architecture: Use this skill to produce a canonical glossary of terms (words and definitions). Use model-domain to stress-test a plan through an interview that resolves domain model decisions. Use deepen-architecture to find module-level refactoring opportunities in the codebase.

HARD GATE — Ubiquitous language is NOT optional. Every term in the domain that could be misunderstood must be glossed. Ambiguity = rework.

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 specs/UBIQUITOUS_LANGUAGE_LATEST.md in the working directory using the format below
  5. Output a summary inline in the conversation

Output Format

Write a specs/UBIQUITOUS_LANGUAGE_LATEST.md file with this structure:

md
# 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."

## Flagged ambiguities

- "account" was used to mean both **Customer** and **User** — these are distinct concepts.

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, call it out in "Flagged ambiguities" with a clear recommendation.
  • Only include terms relevant for domain experts. Skip names of modules or classes unless they have domain meaning.
  • 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.
  • Group terms into multiple tables when natural clusters emerge. One table is fine if terms are cohesive.
  • Write an example dialogue. 3–5 exchanges between a dev and domain expert showing terms used precisely.

Re-running

When invoked again in the same conversation:

  1. Read the existing specs/UBIQUITOUS_LANGUAGE_LATEST.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

© danielvm-git, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/define-language of danielvm-git/bigpowers.

Open the folder on GitHubat commit 812d57a

Compare with similar skills

Define Language next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Define Language compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Define Language this skilldanielvm-git/bigpowers257—~994Automated safety check: PassMIT
Domain Modelingfossasia/eventyay-interpretation1.6k31 repos~821Automated safety check: PassApache-2.0
Architecture Governancezai-org/ZCode7.5k—~1.2kAutomated safety check: PassApache-2.0
Evolutionary Modular Architecturetech-leads-club/agent-skills7k—~3.7kAutomated safety check: PassCC-BY-4.0
Domain Modelingbrim-borium/spotify_sdk1665 repos~806Automated safety check: PassApache-2.0
Domain Modeling and Glossarywindmill-labs/windmill18k—~622Automated safety check: PassCustom licence

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Categories

Questions about Define Language

What does Define Language do?

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Define Language is an agent skill from danielvm-git/bigpowers. Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms.

When should I use Define Language?

Define Language fits situations like: user wants to define domain terms; build a glossary; harden terminology; create a ubiquitous language.

How do I install Define Language in Claude Code?

Run `npx skills add danielvm-git/bigpowers --skill define-language -a claude-code`. Or copy the skill folder (skills/define-language in danielvm-git/bigpowers) into .claude/skills/define-language in your project. Claude Code loads it when a task matches its description.

How do I install Define Language in Codex?

Run `npx skills add danielvm-git/bigpowers --skill define-language -a codex`. Or copy the skill folder (skills/define-language in danielvm-git/bigpowers) into .agents/skills/define-language in your project. Codex loads it when a task matches its description.

Can I use Define Language in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add danielvm-git/bigpowers --skill define-language -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/define-language, .gemini/skills/define-language, .github/skills/define-language and .opencode/skills/define-language in your project.

What does Define Language need to run?

SKILL.md names no scripts, command-line tools or credentials: Define Language is instructions for the agent only.

Does Define Language access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Define Language safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Define Language use?

Define Language is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Define Language use?

About 994 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Define Language?

Skills that share tags, products or a category with Define Language: Domain Modeling (fossasia/eventyay-interpretation, 1.6k stars), Architecture Governance (zai-org/ZCode, 7.5k stars), Evolutionary Modular Architecture (tech-leads-club/agent-skills, 7k stars) and Domain Modeling (brim-borium/spotify_sdk, 166 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Define Language?

danielvm-git (a GitHub user) maintains it in danielvm-git/bigpowers, which has 257 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on September 21, 2026.

Source: danielvm-git/bigpowers on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.