Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/tacc/hpcperfstats/django-python-cursor-rulesgit clone --depth 1 https://github.com/TACC/HPCPerfStatsWhat 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 | $0.01088 | $0.01088 |
| Opus 5 | $0.00544 | $0.00544 |
| Sonnet 5 | $0.00218 | $0.00218 |
| Haiku 4.5 | $0.00109 | $0.00109 |
Grade A, and why
django-python-cursor-rules 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 2d 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.
The source is not reproduced here
Licensed LGPL-2.1
The repository is licensed LGPL-2.1, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 2d ago First seen · 68 lines · 1,088 tokens per session scan A a1464eacdf09
django-python-cursor-rules is a cursor rule published in the GitHub repository TACC/HPCPerfStats (58 stars, last pushed 2d ago), licensed LGPL-2.1. It adds 1,088 tokens to every session, about $0.0054 per session on Opus 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 cursor rules, from other repositories
js-sdk-genai-framework-instrumentation
Guide for implementing JS SDK agent and framework instrumentations, such as LangChain, LangGraph, OpenAI Agents, Claude Agent SDK, Google ADK, and Vercel AI.
coding-agents-hook
Authoring and testing coding-agent hook adapters, including payload probing, session state, capture modes, and plugin manifests. Consult the telemetry convention when changing canonical attributes.
coding-agents-convention
Canonical coding-agent telemetry schema, inbound mappings, and data contracts. Applies to semantic conventions, emission, processing, and readers—not hook implementation mechanics.
security-testing
Authorization, input validation, CE boundary, secrets, and test guidance for OpenLIT server code.
documentation
Standards for OpenLIT documentation, MDX structure, navigation, examples, and terminology.
experimentation-and-metrics
Use when planning or evaluating experiments, A/B tests, or UX metrics. Covers hypotheses, success metrics, and interpretation.