model-domain

A guided review of a software plan against the project’s existing business concepts, terminology, and documented design decisions.

In plain words
What is it for?
Use it to decide core rules, record required conditions and allowed state changes, and update the project’s technical specifications and architecture decisions.
Why use it?
It exposes unclear definitions and conflicting assumptions before they become implementation problems.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/danielvm-git/bigpowers/model-domain
Any agent
npx skills add danielvm-git/bigpowers --skill model-domain
Clone the repo
git clone --depth 1 https://github.com/danielvm-git/bigpowers

Made for: Claude Code, Codex.

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,403 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00060 $0.02403
Opus 5 $0.00030 $0.01202
Sonnet 5 $0.00012 $0.00481
Haiku 4.5 $0.00006 $0.00240

Measured 2d ago against content hash 2eaa53b63fd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

model-domain 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 2d 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.

.cline/skills/model-domain/SKILL.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Model Domain

Distinct from define-language and deepen-architecture: Use this skill to stress-test a plan through a grilling interview that resolves domain model decisions and captures invariants. Use define-language to produce a canonical glossary of terms. Use deepen-architecture to find module-level refactoring opportunities in code.

Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.

HARD GATE — Capture invariants (what MUST always be true) and state machines (what transitions are legal) for core entities. If these are fuzzy, design will fail.

Ask the questions one at a time, waiting for feedback on each question before continuing.

If a question can be answered by exploring the codebase, explore the codebase instead.

Domain awareness

During codebase exploration, also look for existing documentation:

File structure

Most repos have a single context:

/
├── specs/
│   ├── CONTEXT.md
│   └── adr/
│       ├── 0001-event-sourced-orders.md
│       └── 0002-postgres-for-write-model.md
└── src/

If a specs/tech-architecture/tech-stack.md exists, the repo has multiple contexts. The map points to where each one lives:

/
├── specs/
│   ├── CONTEXT-MAP.md
│   └── adr/                          ← system-wide decisions
└── src/
    ├── ordering/
    │   └── specs/
    │       ├── CONTEXT.md
    │       └── adr/                  ← context-specific decisions
    └── billing/
        └── specs/
            ├── CONTEXT.md
            └── adr/

Create files lazily — only when you have something to write. If no specs/tech-architecture/tech-stack.md exists, create it when the first term is resolved. If no specs/adr/ exists, create it when the first ADR is needed.

During the session

Challenge against the glossary

When the user uses a term that conflicts with the existing language in specs/tech-architecture/tech-stack.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"

Read the full file on GitHub · 233 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. 2d ago First seen · 233 lines · 60 tokens per session scan A 2eaa53b63fd2

Subscribe to this mod's changes

model-domain is a skill published in the GitHub repository danielvm-git/bigpowers (156 stars, last pushed 25d ago), licensed MIT. It adds 60 tokens to every session and 2,403 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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