Borrowing it
Nothing to install: this file belongs to stevesolun/ctx. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/stevesolun/ctx/main/.agents/skills/domain-modeling/SKILL.mdgit clone --depth 1 https://github.com/stevesolun/ctxWrote 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/stevesolun/ctx/domain-modeling)<a href="https://agentmods.dev/skills/stevesolun/ctx/domain-modeling"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/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.
<a href="https://agentmods.dev/skills/stevesolun/ctx/domain-modeling"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/domain-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00326 |
| Opus 5.5 | $0.00017 | $0.00130 |
| Sonnet 5.5 | $0.00008 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00033 |
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 1mo 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
Model the domain
Build a precise shared understanding of the concepts that matter to the current decision. Read existing glossaries, context maps, ADRs, code, and tests when they provide relevant evidence.
Sharpen the model
- Identify overloaded terms, hidden distinctions, and conflicting definitions.
- Use concrete scenarios and edge cases to test whether concepts and boundaries hold.
- Compare the stated model with behavior in the code and surface material contradictions.
- Propose clear language when ambiguity is blocking progress, while respecting established repository terminology that remains accurate.
Ask the user to resolve a term only when their intent cannot be inferred safely and the distinction affects the outcome.
Record durable knowledge proportionally
Update a glossary or context map when the user requests it or when a resolved term is durable, project-specific, and useful beyond the current conversation. Follow an existing repository format first; otherwise use the context format as a lightweight starting point.
Record an ADR only when a decision is costly to reverse, surprising without its context, and based on a meaningful tradeoff. Follow existing ADR conventions or use the ADR format. Do not create artifacts merely to complete the workflow.
Keep domain definitions separate from implementation plans. Report unresolved ambiguity and artifact changes explicitly.
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.
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.
- 1mo ago First seen · 39 lines · 42 tokens per session scan A acf707b820e8
domain-modeling is a skill published in the GitHub repository stevesolun/ctx (589 stars, last pushed 11d ago), licensed MIT. It adds 42 tokens to every session and 326 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
vuln-scanner
Audit trending repos for real security vulnerabilities and disclose responsibly - scan and route findings (PVR / dependency PR), re-submit queued advisories, and send armed email disclosures.
fork-fleet
Fork divergence monitor - tracks where the fleet's active forks diverge in CODE (unique commits, new/modified skills) and CONFIG (enable/var/model/schedule vs upstream), gated on real change.
pack-submit
Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR.
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
token-pick
One token recommendation and one prediction market pick - scored, quantified, with a skip branch when signals are weak.
autoresearch
Evolve a skill by generating variations, evaluating them, and updating the best version.