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/linkpranay-ai/context-engineering-protocol/demo-write-user-storiesgit clone --depth 1 https://github.com/linkpranay-ai/context-engineering-protocolWrote 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/rules/linkpranay-ai/context-engineering-protocol/demo-write-user-stories)<a href="https://agentmods.dev/rules/linkpranay-ai/context-engineering-protocol/demo-write-user-stories"><img src="https://agentmods.dev/badge/rules/linkpranay-ai/context-engineering-protocol/demo-write-user-stories.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.00119 |
| Opus 5 | $0.00029 | $0.00060 |
| Sonnet 5 | $0.00012 | $0.00024 |
| Haiku 4.5 | $0.00006 | $0.00012 |
Grade A, and why
demo-write-user-stories 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 5d 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
Demo: Writing User Stories (worked example)
This repository packages its capabilities as portable skills for AI
coding agents. Read .github/skills/demo-write-user-stories/SKILL.md and follow it
when this rule applies.
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.
- 5d ago First seen · 12 lines · 58 tokens per session scan A 8f2739a14f2c
demo-write-user-stories is a cursor rule published in the GitHub repository linkpranay-ai/context-engineering-protocol (8 stars, last pushed 2d ago), licensed Apache-2.0. It adds 58 tokens to every session and 119 once invoked, about $0.0003 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 2026-08-31.
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Never attribute commits to AI tools — human author only.
cursorrules
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