vector-hyperbolic
Embed hierarchical data via npx ruvector@0.2.25 embed text and project into the Poincare ball in user code (no --model poincare flag in 0.2.25)
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- 724
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- Security
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/ruvnet/ruflo --skill vector-hyperbolic- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads vector-hyperbolic automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Vector Hyperbolic
Embed hierarchical data in the Poincare ball model using ruvector.
When to use
Use this skill when your data has inherent hierarchy — dependency trees, module structures, taxonomies, org charts, ontologies. Hyperbolic space captures hierarchical distances with far fewer dimensions than Euclidean embeddings.
Steps
- Ensure ruvector@0.2.25 is available:
npm ls ruvector 2>/dev/null | grep '0.2.25' || npm install ruvector@0.2.25 - Generate a base ONNX embedding (ruvector@0.2.25 does not expose a
--model poincareflag onembed text):npx -y ruvector@0.2.25 embed text "hierarchical concept" -o concept.vec.json - Project into the Poincare ball in your own code (or via the experimental neural substrate):
For an ad-hoc projection, normalize the 384-dim vector to live inside the unit ball (
npx -y ruvector@0.2.25 embed neural --helpx_i / (||x|| * (1 + epsilon))) and persist the projected coordinates alongside the original embedding. - Geodesic distance:
d(u, v) = arcosh(1 + 2 * ||u-v||^2 / ((1-||u||^2)(1-||v||^2)))Distance grows logarithmically with tree depth, preserving hierarchy. - Store results:
mcp__plugin_ruflo-core_ruflo__memory_store({ key: "hyperbolic-CONCEPT", value: "COORDINATES_AND_NEIGHBORS", namespace: "hyperbolic-embeddings" })
Caveats
- ruvector@0.2.25 has no first-class Poincare ball CLI flag. Treat hyperbolic projection as a post-processing step over a standard ONNX embedding.
- If you need a hyperbolic search index, store projected coordinates in AgentDB and compute geodesic distance in your own retrieval code.
Poincare ball properties
| Property | Meaning |
|---|---|
| Norm close to 0 | Generic, root-level concept |
| Norm close to 1 | Specific, leaf-level concept |
| Small geodesic distance | Closely related in hierarchy |
| Large geodesic distance | Distant or different subtrees |
Use cases
- Dependency analysis: embed module imports to find tightly coupled subtrees
- Code architecture: map class hierarchies to discover structural patterns
- Knowledge organization: embed concepts to reveal taxonomic relationships
- Codebase navigation: find most specific/general modules relative to a query
FAQ
What does the vector-hyperbolic skill do?
Embed hierarchical data via npx ruvector@0.2.25 embed text and project into the Poincare ball in user code (no --model poincare flag in 0.2.25)
How do I install vector-hyperbolic?
Run npx skills add https://github.com/ruvnet/ruflo --skill vector-hyperbolic in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/vector-hyperbolic/ (personal) or .claude/skills/vector-hyperbolic/ (project).
Which AI agents can use vector-hyperbolic?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is vector-hyperbolic safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains vector-hyperbolic?
It is published by ruvnet in ruvnet/ruflo. It has 724 recorded installs.
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