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/baodq97/open-plugin/domain-decomposenpx skills add baodq97/open-plugin --skill domain-decomposegit clone --depth 1 https://github.com/baodq97/open-pluginWrote 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/baodq97/open-plugin/domain-decompose)<a href="https://agentmods.dev/skills/baodq97/open-plugin/domain-decompose"><img src="https://agentmods.dev/badge/skills/baodq97/open-plugin/domain-decompose.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 | $0.00199 | $0.02566 |
| Opus 5 | $0.00100 | $0.01283 |
| Sonnet 5 | $0.00040 | $0.00513 |
| Haiku 4.5 | $0.00020 | $0.00257 |
Grade A, and why
domain-decompose 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Decompose
Turn a prose domain/requirements description into a Domain-Driven Design decomposition — bounded contexts → aggregates → entities, value objects, and domain events — named in the business's ubiquitous language; each context doubles as a candidate service boundary on the monolith → microservices path.
Strategic-then-tactical and hybrid: produce a first-pass model from what you're given, then ask targeted questions only where boundaries or ownership are genuinely ambiguous — don't re-ask what the description already settles, and never invent business rules.
Inputs
A domain description: feature list, PRD, process narrative, key capabilities, actors, notable events. If the user points at code instead, say this skill models from domain knowledge, not code, and ask for a description (or the key capabilities and rules) — reverse-engineering a codebase is out of scope.
Brownfield (the model lives only in code, nothing written down): don't reverse it from the code. Ask for a one-page sketch — main capabilities, key events (past-tense things that happen), any hard rules — enough for a first-pass model; step 5 refines the rest. If domain docs/PRDs do exist, step 1 already picks them up.
Reference files (read as needed)
references/ddd-methodology.md— theory and heuristics behind every step (sub-domain types, boundary heuristics, aggregate/entity/VO/event criteria, naming). Read when a judgement call needs grounding.references/bounded-context-canvas.md— template + guidance for each context'sREADME.md.references/aggregate-design-canvas.md— template + rules for modelling each aggregate.references/output-template.md— the exact output contract (where to write, file layout, schemas, frontmatter, hard rules). Read before emitting anything.
Process
1. Find & reconcile existing domain artifacts
Before modelling, look for existing domain knowledge — re-deriving it wastes effort and risks
contradicting what the team already agreed. Look for PRDs, specs, design docs (docs/specs/,
docs/**/prd/, anything titled "… domain model"), code carrying a domain layer (*/domain/,
*/ports/), and this skill's own prior output in docs/domain/. Treat any you find as
authoritative input: build on them, preserve their names and stated rules verbatim, reconcile
rather than re-invent. Prior docs/domain/ output puts you in update mode — you're merging a
delta, not writing from scratch; step 6 handles it.
What ships with it
4 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.
- 4d ago First seen · 196 lines · 199 tokens per session scan A b68d780b7791
domain-decompose is a skill published in the GitHub repository baodq97/open-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 199 tokens to every session and 2,566 once invoked, about $0.0010 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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