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-consume-contextgit 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-consume-context)<a href="https://agentmods.dev/rules/linkpranay-ai/context-engineering-protocol/demo-consume-context"><img src="https://agentmods.dev/badge/rules/linkpranay-ai/context-engineering-protocol/demo-consume-context.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 | $0.00051 | $0.00113 |
| Opus 5 | $0.00026 | $0.00056 |
| Sonnet 5 | $0.00010 | $0.00023 |
| Haiku 4.5 | $0.00005 | $0.00011 |
Grade A, and why
demo-consume-context 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: Consuming a Context Package (worked example)
This repository packages its capabilities as portable skills for AI
coding agents. Read .github/skills/demo-consume-context/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 · 51 tokens per session scan A f942d753c7f4
demo-consume-context 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 51 tokens to every session and 113 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.
Other cursor rules, from other repositories
archcore-context
Archcore knowledge base context — document types, MCP tools, and conventions for working with .archcore/ documents.
aictx
Cursor rule "aictx" from oldskultxo/aictx, covering aictx, priority model, default loop, inspection and advanced tools and what to record.
tell-plumbing-reference
Peer plumbing reference memory for platform/MCP/auth/design-flow plans — never name the peer in commits.
karpathy-guardrails
Karpathy coding guardrails — think first, simplicity, surgical changes, goal-driven.
agentmemory
AgentMemory MCP server rules — use addmemory before answering any question that introduces a project-specific convention, dependency, or constraint.
broken
globs: ["src/ alwaysApply: yes description: testing rules -.