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> **Version:** 0.4.0-draft | **Status:** π Open Standard, seeking collaborators
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> **Version:** 0.5.0-draft | **Status:** π Open Standard, seeking collaborators
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βοΈ **Write once. Deploy to any agent platform.**
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@@ -19,6 +19,7 @@ Managing AI agent artifacts at scale is a structural mess:
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- π₯ **No composability** β loading multiple packages causes silent instruction conflicts with no namespacing.
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- βοΈ **No lifecycle management** β platforms lack hooks for events like `pre-tool-use` or `permission-request` that deterministic agent validation requires.
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- π **No update management** β there is no standard mechanism to propagate fixes or new versions of skills across projects; every consumer must update manually and in isolation.
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- π§ͺ **No testability** β there is no standard way to verify that a skill or hook works correctly. Scripts lack test harnesses, and LLM-driven behavior has no eval framework β breakage is discovered in production.
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- π‘οΈ **Uncontrolled duplication creates security risk** β skills are copy-pasted across repositories with no traceability. Since skills can contain executable scripts, a single compromised or outdated copy can go undetected across dozens of projects, expanding the attack surface with every duplicate.
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### π€ Why "Hacking" npm Is Not Enough
@@ -77,6 +78,7 @@ A single `package.agent.json` manifest declares your artifact and makes it consu
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| π **Deterministic Resolution**| Lock files guarantee reproducible agent behavior in CI |
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