iolairus/borderlint

A tool for mapping where your AI data flows and governing it against your residency and sovereignty policy

7Stars on the repository
34Mods indexed here, across every type
9d agoLast push, which is what freshness is scored on
MITLicence, which decides whether bodies are shown

iolairus/borderlint

Skill Claude CodeCodex

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

7 9d ago A 31 tokens copy · 100% MIT

iolairus/borderlint

Skill Claude CodeCodex

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

7 9d ago A 31 tokens copy · 100% MIT

openspec-explore

03

iolairus/borderlint

Skill Claude CodeCodex

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

7 9d ago A 39 tokens copy · 100% MIT

openspec-propose

04

iolairus/borderlint

Skill Claude CodeCodex

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

7 9d ago A 47 tokens copy · 100% MIT

openspec-sync-specs

05

iolairus/borderlint

Skill Claude CodeCodex

Sync delta specs from a change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change.

7 9d ago A 38 tokens copy · 100% MIT

iolairus/borderlint

Skill Claude CodeCodex

Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.

7 9d ago A 32 tokens copy · 80% MIT

borderlint-check

07

iolairus/borderlint

Skill Claude CodeCodex

Run borderlint before adding any AI SDK, AI endpoint, or model identifier to the codebase. Use whenever a change introduces an AI provider dependency, an LLM endpoint or baseurl, or a model id — check residency, sovereignty, and provenance before the code is committed.

7 9d ago A 60 tokens original MIT