PyGraphistry is a Python library for loading, preparing, analyzing, and exploring large graphs through Graphistry’s GPU-accelerated visual graph analyzer. Data scientists and developers use it with dataframes, graph databases, and tools such as Pandas, Spark, RAPIDS, and Apache Arrow. Catalogue add-ons support workflows around using the library.
Borrowing it
Nothing to install: this file belongs to graphistry/pygraphistry. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/graphistry/pygraphistry/master/AGENTS.mdgit clone --depth 1 https://github.com/graphistry/pygraphistryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/graphistry/pygraphistry/agents-md)<a href="https://agentmods.dev/instructions/graphistry/pygraphistry/agents-md"><img src="https://agentmods.dev/badge/instructions/graphistry/pygraphistry/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/graphistry/pygraphistry/agents-md"><img src="https://agentmods.dev/badge/instructions/graphistry/pygraphistry/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00337 | $0.00337 |
| Opus 5.5 | $0.00135 | $0.00135 |
| Sonnet 5.5 | $0.00067 | $0.00067 |
| Haiku 4.5 | $0.00034 | $0.00034 |
Grade A, and why
pygraphistry AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 15d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
AGENTS.md
This file defines AI assistant guidance for this repository.
Skill Locations
Canonical skills live under:
.agents/skills/
Platform Path Conventions
- OpenAI Codex: uses
.agents/skills/ - Claude Code: often uses
.claude/skills/ - Other tools (Cursor/Copilot/etc.): may use
.agents/skills/or tool-specific paths
Recommended local setup:
# Claude path to shared skills
mkdir -p .claude
ln -s ../.agents/skills .claude/skills
Guidance Priority
- Follow repository docs and tests as source of truth.
- Keep edits minimal and verifiable.
- Run relevant lint/tests for touched areas.
Release Assistant Reminder
- During publish assistance, after pushing tag
X.Y.Z, always check.github/workflows/publish-pypi.ymlrun state. - Treat
Publish distribution to PyPIinwaitingas an expected manual gate for environmentpypi-release; explicitly instruct maintainer to clickReview deploymentsbefore expecting PyPI completion. - After the workflow completes, verify both TestPyPI and PyPI public metadata report
X.Y.Z; PyPI may lag briefly after the job succeeds. - Create or verify the matching GitHub Release for tag
X.Y.Z, then check Read the Docs.latestmay update automatically, while tag-specific versions can require maintainer activation in the RTD dashboard. - Record release follow-ups discovered during readiness audits as issues in the owning repo before final handoff.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 15d ago Changed · -11 lines · -62 tokens per session e2b45ae1cdd5
- 2mo ago First seen · 49 lines · 399 tokens per session scan A 761e39fcfa44
pygraphistry AGENTS.md is an instructions file published in the GitHub repository graphistry/pygraphistry (2,576 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 337 tokens to every session, about $0.0013 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.