GocciaScript: Skill for Codex

.agents/skills/domain-modeling/SKILL.md

domain-modeling is a skill for Codex from frostney/GocciaScript. It costs 35 tokens per session (781 once invoked), scanned A, a copy of domain-modeling, MIT.

A guide for defining the important concepts and boundaries in a software project. It records agreed terminology and architectural decisions in files such as CONTEXT.md and ADRs, which are written records of decisions.

In plain words
What is it for?
Use it when shaping domain terminology, resolving ambiguous concepts, or recording a significant technical decision. It can create and update project context and decision records.
Why use it?
It prevents developers and coding agents from using the same words to mean different things or making conflicting design choices. The shared notes keep the project model clear as it changes.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

This is frostney/GocciaScript's own configuration. It tells Codex how to work on GocciaScript itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything GocciaScript configures →

Reuse

Borrowing it

Nothing to install: this file belongs to frostney/GocciaScript. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/frostney/GocciaScript/main/.agents/skills/domain-modeling/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/frostney/GocciaScript

Made for: Codex.

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 domain-modeling

README.md
[![agentmods](https://agentmods.dev/badge/skills/frostney/gocciascript/domain-modeling/github.svg)](https://agentmods.dev/skills/frostney/gocciascript/domain-modeling)
Your own site
<a href="https://agentmods.dev/skills/frostney/gocciascript/domain-modeling"><img src="https://agentmods.dev/badge/skills/frostney/gocciascript/domain-modeling/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 domain-modeling

Your own site · 80×15
<a href="https://agentmods.dev/skills/frostney/gocciascript/domain-modeling"><img src="https://agentmods.dev/badge/skills/frostney/gocciascript/domain-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 781 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 $0.00035 $0.00781
Opus 5.5 $0.00014 $0.00312
Sonnet 5.5 $0.00007 $0.00156
Haiku 4.5 $0.00003 $0.00078

Measured 22d ago against content hash 7b925d7b1e34, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

domain-modeling 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 22d 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 domain-modeling — 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.

.agents/skills/domain-modeling/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Domain Modeling

Actively build and sharpen the project's domain model as you design. This is the active discipline: challenging terms, inventing edge-case scenarios, and writing the glossary and decisions down the moment they crystallise. (Merely reading GLOSSARY.md for vocabulary is not this skill: that's a one-line habit any skill can do. This skill is for when you're changing the model, not just consuming it.)

File structure

Most repos have a single context:

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

If a GLOSSARY-MAP.md exists at the root, the repo has multiple contexts. The map points to where each one lives:

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

Create files lazily: only when you have something to write. If no GLOSSARY.md exists, create one when the first term is resolved. If no docs/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 GLOSSARY.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y. Which is it?"

Sharpen fuzzy language

When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account': do you mean the Customer or the User? Those are different things."

Discuss concrete scenarios

When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.

Cross-reference with code

When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible. Which is right?"

Read the full file on GitHub · 75 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 22d ago Changed · +1 tokens per session 7b925d7b1e34
  2. 29d ago Changed 327a2b50620e
  3. 1mo ago First seen · 75 lines · 34 tokens per session scan A 9617041db9b0

Subscribe to this mod's changes

domain-modeling is a skill published in the GitHub repository frostney/GocciaScript (20 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 781 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to domain-modeling, differing in 0 lines, and is treated as a copy.

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