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.
npx agentmods add skills/hecer/yoke/domain-modelingnpx skills add HECer/yoke --skill domain-modelinggit clone --depth 1 https://github.com/HECer/yokeWrote 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.
[](https://agentmods.dev/skills/hecer/yoke/domain-modeling)<a href="https://agentmods.dev/skills/hecer/yoke/domain-modeling"><img src="https://agentmods.dev/badge/skills/hecer/yoke/domain-modeling.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.00395 |
| Opus 5 | $0.00028 | $0.00198 |
| Sonnet 5 | $0.00011 | $0.00079 |
| Haiku 4.5 | $0.00006 | $0.00040 |
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 5d 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.
What it actually says
Domain modeling
Build the model actively: challenge terms, test relationships with concrete scenarios, compare the stated behavior with code, and record a term when it becomes settled.
Yoke stores durable context under .yoke/context/:
GLOSSARY.mdis the canonical language for a single domain context.CONTEXT-MAP.mdis optional and maps multiple domain contexts plus their relationships.DECISIONS.mdrecords durable outcomes and ADR-class trade-offs.
Read the existing files before proposing vocabulary. Merely consuming their terms is a normal context habit, not a reason to run this skill.
Workflow
- Identify overloaded, vague, conflicting, or missing terms in the request and current glossary.
- Propose one canonical term and name avoidable aliases. Ask when the distinction changes behavior.
- Stress-test relationships with specific scenarios, especially partial, repeated, failed, and cross-context cases.
- Compare the model with public interfaces, persistence shapes, and relevant tests. Surface a contradiction instead of silently choosing one side.
- When a term is settled, update
GLOSSARY.mdimmediately using CONTEXT-FORMAT.md. Preserve unrelated entries. - Update
CONTEXT-MAP.mdonly when the repository contains more than one genuine domain context. - Record an ADR-class decision only when all three thresholds in ADR-FORMAT.md pass.
Glossary definitions describe the domain, not its implementation. General programming concepts do not belong there.
What ships with it
2 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.
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.
- 5d ago First seen · 36 lines · 57 tokens per session scan A eedfee989f0a
domain-modeling is a skill published in the GitHub repository HECer/yoke (2 stars, last pushed 3d ago), licensed MIT. It adds 57 tokens to every session and 395 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 2026-08-31.
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