.claude/skills/distillRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
Session knowledge distillation: assign what you just learned in this session into an agent's four-layer persistent knowledge base (rule / memory / skill / decision record). The core is four disciplines — search before adding, pick the right layer, guard against bloat, and run a hygiene pass before landing anything. Fits agent workflows that already have (or want to build) these four layers; this is not a general note- taking tool. Invoke explicitly at the end of a session to consolidate what was learned.
These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.
These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/distillRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/distillRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/distillRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.
clawhub install @xiaoba-dev/distillclawhub inspect @xiaoba-dev/distill --version 2.0.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.
The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.
sha256:9ea6f1744d463c73ec6a676d7ed358521840abbe50a99c0d57320e1d99aa10e4skill-card.mdSKILL.mdFull English rewrite. Same four-layer framework, same core discipline (search before adding, pick the right layer, guard against bloat, hygiene pass before landing), same two anonymized case studies (the generic lesson trapped in the wrong bucket, the duplicate/contradictory knowledge base) - only the language changed.