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 skills add soulcodex/agentic --skill ddd-aggregate-modelinggit clone --depth 1 https://github.com/soulcodex/agenticWrote 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/soulcodex/agentic/ddd-aggregate-modeling)<a href="https://agentmods.dev/skills/soulcodex/agentic/ddd-aggregate-modeling"><img src="https://agentmods.dev/badge/skills/soulcodex/agentic/ddd-aggregate-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/soulcodex/agentic/ddd-aggregate-modeling"><img src="https://agentmods.dev/badge/skills/soulcodex/agentic/ddd-aggregate-modeling.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00062 | $0.00678 |
| Opus 5.5 | $0.00025 | $0.00271 |
| Sonnet 5.5 | $0.00012 | $0.00136 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
ddd-aggregate-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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DDD Aggregate Modeling Skill
Step 1 - Define Context and Ubiquitous Language
- Identify the bounded context owning the behavior.
- Name entities, value objects, and commands using domain language.
- Reject generic names (
Manager,Helper,Data) unless they are domain terms.
Step 2 - Choose the Aggregate Root
- Pick one root that owns consistency for the invariant set.
- Ensure external callers reference only root IDs, not child internals.
- Keep the aggregate small; if many transactions touch disjoint invariants, split aggregates.
Step 3 - Classify Members Correctly
Use this decision table:
| Case | Model as |
|---|---|
| Needs identity inside aggregate lifecycle | Child Entity |
| Structural equality only, immutable meaning | Value Object |
| External persistence detail | Adapter DTO / Row Model (not domain) |
Value object categories to model explicitly:
- constrained strings (
Email,Name,VatId) - bounded numbers/ranges (
Lanes,Port,Quantity) - enumerations (
Language,Role,SystemType)
Step 4 - Encode Invariants in Domain Behavior
- Validate on constructor/factory and on every mutating method.
- Keep aggregate state private; expose intent methods (
Create,Update,Delete,Verify). - Guard temporal ordering when needed (ignore/reject stale updates deterministically).
- Keep authorization outside entities; enforce in application handlers.
Step 5 - Model Snapshot/Primitives Boundaries
- Add explicit primitives/snapshot structures for adapter boundaries.
- Use
ToPrimitives/SnapshotandFromPrimitives/RestoreFromSnapshot. - Do not pass transport or ORM models directly into domain behavior.
- Keep mapping explicit; avoid reflection-based generic mappers.
Step 6 - Define Repository and Collection Contracts
- Define repository interfaces in domain/application, implementations in infrastructure.
- Split reader/writer contracts when beneficial.
- Return aggregates or domain collections, not adapter structs.
- Add domain collections when query semantics have domain meaning.
What ships with it
1 file 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 · 84 lines · 62 tokens per session scan A f1dfe2c3aff6
ddd-aggregate-modeling is a skill published in the GitHub repository soulcodex/agentic (10 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 678 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 2026-08-31.
Other skills, from other repositories
domain-modeling
DDD practical guide: Event Storming, Bounded Contexts, Aggregates and domain-driven design patterns.
write-microflows
Microflow syntax reference in MDL — every activity type, control flow, expressions, and the mistakes that fail mxcli check. Use before writing any CREATE MICROFLOW, and when debugging a microflow syntax error.
database-connections
Connect a Mendix app to an external database over JDBC with the External Database Connector, and define the queries microflows run against it. Use when the app must read or write Oracle, PostgreSQL, MySQL or SQL Server directly from a microflow.
java-actions
Create and call custom Java actions — extending Mendix with server-side Java, and invoking those actions from microflows in MDL. Use when logic needs a Java library, an algorithm microflows cannot express, or an integration only available in Java.
json-structures-and-mappings
Create and manage JSON structures, import mappings and export mappings in MDL, plus the domain-model shapes they map onto. Use when turning a JSON payload into entities, mapping a REST or queue response, or exporting objects as JSON.
rest-client
Call external REST APIs from Mendix — the three approaches (inline REST CALL, consumed REST client document, generated from OpenAPI) and how to choose. Use when integrating with any external REST API, or when a published REST service's custom-authentication microflow reads a token from a header or the query string.