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book-ddd-distilled-modeling skillA

book-ddd-distilled-modeling is agent-read markdown (skill) from kunolu/640-skills: Guides lightweight domain modeling with ubiquitous language, bounded contexts, and subdomain focus. Always run after every completed grill-with-docs session as an independent second-pass boundary review; also use before PRD, design, or implementation when domain ambiguity exists..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Book DDD Distilled Modeling

Use this Skill to sharpen domain language before turning a business request into PRD, issues, design, or code.

It is derived from the `mini` rule style of `agent-rules-books` and should run after project evidence is read. It complements `grill-with-docs`, `to-spec`, and task planning.

## Mandatory Post-grill Review

Every fully completed `grill-with-docs` session MUST be followed immediately by this Skill, whether the Agent initiated that session or the user invoked it explicitly. The `domain-modeling` activity embedded in `grill-with-docs` is the active interview-time modeling pass; it does not satisfy or replace this independent second-pass review.

Re-read the completed clarification result and the supporting project facts. Look for boundary errors, hidden term collisions, unsupported invariants, misplaced responsibilities, and unresolved context ownership rather than merely restating the interview.

The review is a gate before requirement confirmation, PRD, design, task creation, or implementation:

- `confirmed`: no unresolved boundary issue prevents the workflow from advancing.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add kunolu/640-skills/book-ddd-distilled-modeling@git:20260920.f9bbb90
Exact content
mdr add kunolu/640-skills/book-ddd-distilled-modeling@sha256:c93bc44e6005c1fc

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_6vfbp6dhmrogekxh.svg)](https://markdownregistry.com/a/art_6vfbp6dhmrogekxh)

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Versions

versioncommittedcommitsizeaudit
git:20260920.f9bbb90 latest2026-09-20 f9bbb90 4,114 BA view · diff
git:20260719.63495402026-07-19 6349540 4,133 BA view · diff
git:20260718.951ea5b2026-07-18 951ea5b 2,143 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (4114 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

kunolu/640-skills · 113 stars · license Apache-2.0 · pushed 2026-09-25 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_6vfbp6dhmrogekxh
GET https://markdownregistry.com/api/v1/resolve?ref=kunolu/640-skills/book-ddd-distilled-modeling
GET https://markdownregistry.com/api/v1/blob/c93bc44e6005c1fc3af82c0aa23e0aff877f121a03ead74e08b1e2bc1e2e8f7e

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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