Loading Addressable Markdown
SkillDocs & knowledgeUse when a mission, slice, dashboard, or task references Markdown as path#h2-slug or path#h2-slug/h3-slug outside the OpenRig context-pack library.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Loading Addressable Markdown skill
What this skill tells your AI
The instructions your AI receives, as published by mvschwarz/openrig in packages/daemon/assets/plugins/openrig-core/skills/loading-addressable-markdown/SKILL.md and read by ahel’s review.
Overview
Load exactly one addressed Markdown section from any filesystem tree. The resolver mirrors OpenRig's shipped H2/H3 grammar without requiring the file to live in the context library.
Use
Run the bundled script. Relative file references resolve from --root; without it they resolve from the current directory.
node ~/.agents/skills/loading-addressable-markdown/scripts/resolve-markdown.mjs \
--root /path/to/mission \
'slices/09-source-cleanup/SPEC.md#proposal'
The accepted forms are:
file.md— whole filefile.md#h2-slug— full H2 span, including child sectionsfile.md#h2-slug/h3-slug— full H3 span
Slugs are lowercase; Markdown emphasis/code markers are removed; each other non-alphanumeric run becomes -. Duplicate or missing paths fail loudly. Headings inside fenced code blocks are ignored.
Common mistakes
- Do not use
rig context getfor an arbitrary filesystem path; that command resolves context-library refs. - Do not hand-slice headings with
sedor line numbers; the bundled resolver owns span and fence behavior. - Quote addresses in shell commands.
Signals
- GitHub stars
- 67
- Forks
- 12
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
loading-addressable-markdown- Source
- github.com/mvschwarz/openrig