Portable skill definitions for working with ArrowSpace — a spectral vector search library that goes beyond cosine similarity by incorporating graph Laplacian eigenstructure.
ArrowSpace adds a spectral dimension to vector similarity, enabling search that considers both semantic content and structural role in the dataset.
pip install arrowspaceThen:
from arrowspace import ArrowSpaceBuilder
import numpy as np
items = np.array([[0.1, 0.2, 0.3], [0.0, 0.5, 0.1], [0.9, 0.1, 0.0]], dtype=np.float64)
graph_params = {"eps": 1.0, "k": 6, "topk": 3, "p": 2.0, "sigma": 1.0}
aspace, gl = ArrowSpaceBuilder().build(graph_params, items)
query = np.array([0.05, 0.2, 0.25], dtype=np.float64)
hits = aspace.search(query, gl, tau=1.0)
print(hits) # [(0, 0.99), (1, 0.76), (2, 0.22)]| Resource | Link |
|---|---|
| JOSS paper | doi:10.21105/joss.09002 |
| Rust library | github.com/Mec-iS/arrowspace-rs |
| Python bindings | github.com/tuned-org-uk/pyarrowspace |
| PyPI package | pip install arrowspace |
| crates.io | cargo add arrowspace |
| Presentation 1 | Spectral Indexing overview |
| Presentation 2 | ArrowSpace deep-dive |
| Design article | tuned.org.uk — Part 2: Semantic Basins |
This repo contains skill definitions that teach AI agents how to use ArrowSpace:
| Skill | File | What it covers |
|---|---|---|
| ArrowSpace Core | skills/arrowspace-core.md |
Builder, configuration, building signal graphs |
| Vector Search | skills/arrowspace-search.md |
Querying, λτ scoring, search parameters |
| Spectral Analysis | skills/arrowspace-spectral.md |
Spectral methods, graph characterisation, diffusion |
OpenCode — symlink or copy SKILL.md into .opencode/skills/:
cp SKILL.md .opencode/skills/arrowspace/SKILL.mdClaude Code — reference in CLAUDE.md or add to project instructions.
Copilot / Cursor — include the relevant skills/*.md content in your custom instructions.
Any agent — point it at this repo: "You have access to the ArrowSpace skills at skills/."
Install the skill utilities directly:
pip install arrowspace-skillsfrom arrowspace_skills import (
suggest_params, # heuristic graph parameters
build_index, # one-shot index builder
tune_tau, # grid search over spectral gate
search_with_recall, # query with result cap
item_lambdas, # per-item lambda-tau scores
sorted_lambdas, # lambda-tau-ranked item list
explain_spectral_properties, # eigendecomposition diagnostics
spectral_summary, # human-readable spectral report
)See arrowspace_skills/ for reusable helper functions.
Apache 2.0 — same as arrowspace-rs.