SkillsAdd

graphistry/graphistry-skills

pygraphistry

TOC router for PyGraphistry Python SDK tasks. Use when asked to "plot a graph", "visualize my edges", "load a dataframe into graphistry", "import graphistry", "run UMAP on my graph", "query my graph with GFQL or Cypher", "pick an execution engine", "make my GFQL query faster", "connect graphistry to Neo4j/Splunk/Kusto", or any Python SDK graph workflow. Also triggers on "graphistry.register", "g.plot()", ".gfql()", "chain-list", "hypergraph", "engine='polars'", "polars-gpu", "cudf", or "pygraph…

First seen Mar 3, 2026

Installation

$ npx skills add graphistry/graphistry-skills --skill pygraphistry
View on skills.sh ↗ GitHub repository ↗

Also in this package

Other skills from graphistry/graphistry-skills · top by installs.

npx skills add graphistry/graphistry-skills
pygraphistry-visualization 38 pygraphistry-core 36 pygraphistry-connectors 36 pygraphistry-gfql 35 pygraphistry-ai 35 graphistry-rest-api 27 graphistry 26 eval-otel 2 benchmarks 2 plan 1

Browse all from graphistry/graphistry-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
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GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 2
License LICENSE
Default branch main
Open issues 8
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,095 B
  • docs SUMMARY.md 867 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 35 installs

SKILL.md

PyGraphistry Router

Use this skill as a dispatcher to specialized skills. Treat this as the Python SDK entrypoint; for a cross-interface entrypoint use graphistry.

Route By Intent

  • Setup/auth/first plot from tables: use pygraphistry-core.
  • Direct Graphistry REST endpoint requests (curl, /api/v2/..., JWT/Bearer, upload/session/url params): immediately use graphistry-rest-api and skip ReadTheDocs discovery.
  • Styling/layout/static output/privacy and sharing: use pygraphistry-visualization.
  • Pattern matching, GFQL/Cypher queries, Let/DAG bindings, GRAPH constructors, predicates, remote graph queries, or choosing pandas/polars/cudf/polars-gpu: use pygraphistry-gfql.
  • UMAP/DBSCAN/embedding/anomaly and graph-AI notebooks: use pygraphistry-ai.
  • Database/platform integrations (Neo4j, Splunk, Kusto, Databricks, SQL, etc.): use pygraphistry-connectors.

Fast Targeted Fetch Protocol

  • REST-intent exception: do not run this protocol for REST tasks routed to graphistry-rest-api.
  • Start from references/pygraphistry-readthedocs-toc.md; do not crawl broad docs first.
  • Use references/pygraphistry-readthedocs-top-level.tsv for section-level shortcuts.
  • Pick exactly one primary skill and at most two secondary docs before fetching content.
  • Do one batched discovery read first (TOC + top-level index), then pick targets.
  • After discovery, do at most one deep-page read per iteration.
  • Prefer section indexes (.../gfql/index.html, .../visualization/index.html) before deep pages.
  • For routing replies, prefer ReadTheDocs URLs (https://pygraphistry.readthedocs.io/...) over GitHub/local file paths unless the user explicitly asks for source code links.
  • Keep the first routing response compact (typically 3-5 lines): selected skill + top links.
  • Escalate to deeper page fetches only after the user confirms direction or asks for detail.
  • Avoid serial micro-reads across many files when one batched lookup can answer routing.
  • Avoid blind full dumps (cat *, full sitemap dumps) that bloat context without improving routing quality.
  • For canonical URL verification, prefer local snapshot evidence first; use web fallback when the user requests freshness or local mapping is missing.

Default Safety Rules

  • Read credentials from environment variables; do not hardcode secrets in tracked files.
  • Prefer api=3 for modern features.
  • Prefer a plain type column on both nodes and edges for legend/category defaults.
  • Set explicit privacy mode before sharing links for sensitive data.
  • For large graphs, reduce columns/rows before upload and visualize focused subgraphs first.

Canonical Docs