ddd-advisor
Skill3 starsChanged 52 days agoNo licenceView on GitHub
DDD audit of an existing codebase AND Domain-Driven Design guidance while development is under way. Use as soon as the user mentions DDD, an "anemic domain model", "aggregates", "entities vs value objects", "bounded context", "ubiquitous language", "context map", "anti-corruption layer", or asks a domain modeling question ("where does this domain logic belong?", "is this an entity?", "how do I split this monolith into contexts?"). Use it ALSO when an audit or a remediation surfaces scattered domain logic, leaking layers, or tight coupling between subsystems — even when the word "DDD" is never said. The ai-code-remediation skill invokes it to qualify design symptoms. It reads the codebase-cartographer output when it exists, and hands confirmed boundaries to codebase-harness to become architecture invariants.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ai-code-remediationSkill
- behavior-driven-testingSkill
- clarify-with-choicesSkill
- code-assimilation-quizSkill
- codebase-cartographerSkill
- codebase-harnessSkill
- plan-driven-devSkill
- premerge-reviewSkill
- product-strategySkill
- systematic-debuggingSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.