laws
Skill0 starsChanged 5 months agoMITView on GitHub
List enacted laws and world structures in Gitizens. Must output === CHECK OK. Returns filenames sorted newest first (e.g. ["law-014.md", "law-013.md", ...]). For each of the first 10 filenames: Extract from each law file: - Law number: from # Law NNN: heading - Title: text after # Law NNN: - Enacted date: from **Enacted:** line - Vote counts: from **Vote:** line - Proposed by: from **Proposed by:** line - Proposal issue number: from **Proposal:** line
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 82
Use python3 base64 decode for cross-platform compatibility.
≈ “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.
Files
Skill: gitizens:laws
List enacted laws and world structures in Gitizens.
Setup
GITIZENS_REPO="ordinary9843/gitizens"Steps
Step 1 — Check GitHub CLI access
bash scripts/check-access.shMust output === CHECK OK.
Step 2 — Fetch world state
gh api repos/ordinary9843/gitizens/contents/world/state.json \
--jq '.content' | python3 -c "import sys,base64; sys.stdout.write(base64.b64decode(sys.stdin.read().strip()).decode())"Step 3 — Fetch law file list
gh api repos/ordinary9843/gitizens/contents/world/laws \
--jq '[.[] | select(.name | endswith(".md")) | .name] | sort | reverse'Returns filenames sorted newest first (e.g. ["law-014.md", "law-013.md", ...]).
Step 4 — Fetch up to 10 most recent laws
For each of the first 10 filenames:
gh api repos/ordinary9843/gitizens/contents/world/laws/{filename} \
--jq '.content' | python3 -c "import sys,base64; sys.stdout.write(base64.b64decode(sys.stdin.read().strip()).decode())"Extract from each law file:
- Law number: from
# Law NNN:heading - Title: text after
# Law NNN: - Enacted date: from
**Enacted:**line - Vote counts: from
**Vote:**line - Proposed by: from
**Proposed by:**line - Proposal issue number: from
**Proposal:**line
Step 5 — Display
=== ENACTED LAWS ({total} total) ===
Era: {state.era} | Laws: {state.laws_count} | Last enacted: {state.last_enacted}
Law 014 "Advance to the Early Republic Era"
Enacted: 2026-06-10 | Vote: 1👍 0👎 | Proposed by: @username | Issue: #15
Law 013 "Declare Open Source the Founding Principle"
Enacted: 2026-06-10 | Vote: 1👍 0👎 | Proposed by: @username | Issue: #14
...
(showing most recent 10 — full history: https://github.com/ordinary9843/gitizens/blob/master/history/INDEX.md)
🌐 Watch the world: https://ordinary9843.github.io/gitizens/If no laws:
No laws have been enacted yet. Be the first — run /gitizens:propose.Notes
- Show at most 10 laws to avoid context overflow. Always note how many total exist.
- Use
python3 base64decode for cross-platform compatibility. - Full history including rejected proposals:
history/INDEX.md.
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.

