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/skills/plan/SKILL.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/skills/graphistry/pygraphistry/plan)<a href="https://agentmods.dev/skills/graphistry/pygraphistry/plan"><img src="https://agentmods.dev/badge/skills/graphistry/pygraphistry/plan/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/skills/graphistry/pygraphistry/plan"><img src="https://agentmods.dev/badge/skills/graphistry/pygraphistry/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Memory Poisoning · line 20 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
- medium Agent Snooping · line 73 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00038 | $0.01495 |
| Opus 5.5 | $0.00015 | $0.00598 |
| Sonnet 5.5 | $0.00008 | $0.00299 |
| Haiku 4.5 | $0.00004 | $0.00150 |
Grade A, and why
plan 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 19d 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.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
File-Based Task Plan
Default: Use Platform Planning
Unless explicitly requested ("create a plan.md", "use the plan template"), prefer your AI platform's built-in planning. This file-based approach is only justified for multi-session or handoff work.
Use When
- User explicitly requests it
- Work spans multiple sessions / context resets
- Handoff to another AI or human
- Complex multi-PR coordination
Setup
- Copy template →
plans/[task_name]/plan.md - Replace
[placeholders] - Fill Context sections
- Mark Step 1
🔄 - For multiple checkouts, record the absolute plan path, each worktree root, and base/head SHAs. Link existing handoff plans and preserve completed work; append to shared plans without overwriting concurrent updates.
⚠️ gitignore: plans/ is local only — never commit unless user explicitly requests (git add -f).
Writing Style
Terse but recoverable — every token earns its place, but a cold-start agent with zero context must still understand and resume. Abbreviate, omit filler. Test: would a stranger understand this with no other context? If yes, cut further. If no, add the minimum needed.
Emoji: only use where it saves characters or adds clarity not already present in the text (e.g. status icons replace words, ⚠️ flags a genuine warning). Do not add emoji just to have them — if removing one loses nothing, remove it.
Critical Meta-Goals
This plan MUST be:
- Self-describing — all context to resume is IN THIS FILE and files it points to
- Write before run — record planned action in file before executing
- Update before continuing — record results immediately after, before next step
- Single source of truth — if not in the plan, it didn't happen
- Safe to resume — any agent can pick up by reading only this file
⚠️ External memory is unreliable. This file — and files it points to — are your ONLY memory.
Anti-Drift Protocol
Three Commandments
- RELOAD before every action — memory wiped, plan is all you have
- UPDATE after every action — unwritten = didn't happen
- TRUST ONLY THE PLAN — not memory, not assumptions
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.
- 19d ago Changed · +2 lines 0c3ce6d3dfaf
- 2mo ago First seen · 131 lines · 38 tokens per session scan A 1cb350f6f9fb
plan is a skill published in the GitHub repository graphistry/pygraphistry (2,576 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 38 tokens to every session and 1,495 once invoked, about $0.0002 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.
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