SkillCheatSheet
embedding-anisotropy-check
An AI agent skill from github/awesome-copilot, scored 64 out of 100 by code.
Code score by group
It loses the most points in Done criteria (11), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
Use before reporting any cosine similarity computed over embeddings or transformer hidden states, whether the agent computed the vectors or loaded them. Measures the anisotropy of each side, centres by the population mean, and scores matched pairs against a permuted floor taken from the same comparison. Use when comparing one model's embeddings across precisions, runtimes or layers, when evaluating retrieval, probes or adapters, or before calling a similarity high, two conditions in agreement, or a small gap a null.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- github/awesome-copilot
- Folder
- skills/embedding-anisotropy-check
- License
- MIT
- GitHub stars
- 41,064
- SKILL.md lines
- 106
- Other files
- 2
Add embedding-anisotropy-check to your agent
npx skills add github/awesome-copilot --skill embedding-anisotropy-checkThe command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
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Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.