Explain a technical spec or proposed change in plain language: what problem it solves, how the solution works, and every schema change.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# ELI5
Turn the referenced spec or change into an accurate mental model for a technical
reader who does not live in the code. Plain language, full precision: simplify
the telling, never the claims.
## The Register
Other skills point here when their output must be readable by someone who
didn't live the work. The reader is technical — pseudocode and precise claims
land fine — but they have read none of the code and none of the session's
messages: no diff, no transcript, no labels the work invented along the way.
Writing ELI5 means:
- Walk one concrete scenario end to end — the triggering event, what happens
today, what the change (or the unbuilt alternative) would do — instead of
describing properties in the abstract.
- Define every term of art at first use; never lean on labels the spec, code,
or session invented.
- Use small concrete examples without replacing precise claims with analogies.
- Reach for pseudocode when explaining control flow, ordering, or timing.
Prose describing when-something-fires reads as plausible and hides the gap;
five lines of pseudocode make the gate visible and let the reader see the
…
The line at the top of this page pins the label git:20260813.dbb1aa5, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the 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 (3242 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
dzhng/skills · 1,377 stars · license MIT · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_flpe5vxll2i3vtv7
GET https://markdownregistry.com/api/v1/resolve?ref=dzhng/skills/eli5
GET https://markdownregistry.com/api/v1/blob/268c996bcc62796e31ca74105929c77907e4b4e1abda3341b9a01b9cd2059004
Your AI assistant 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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