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.
git 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/ult-autoscaffold-content)<a href="https://agentmods.dev/rules/linkpranay-ai/context-engineering-protocol/ult-autoscaffold-content"><img src="https://agentmods.dev/badge/rules/linkpranay-ai/context-engineering-protocol/ult-autoscaffold-content/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/rules/linkpranay-ai/context-engineering-protocol/ult-autoscaffold-content"><img src="https://agentmods.dev/badge/rules/linkpranay-ai/context-engineering-protocol/ult-autoscaffold-content.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 | $0.00207 | $0.00266 |
| Opus 5.5 | $0.00083 | $0.00106 |
| Sonnet 5.5 | $0.00041 | $0.00053 |
| Haiku 4.5 | $0.00021 | $0.00027 |
Grade A, and why
ult-autoscaffold-content 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 2mo 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
ult-autoscaffold-content
This repository packages its capabilities as portable skills for AI
coding agents. Read .github/skills/ult-autoscaffold-content/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.
- 2mo ago First seen · 12 lines · 207 tokens per session scan A 0e5d08dacb6e
ult-autoscaffold-content is a cursor rule published in the GitHub repository linkpranay-ai/context-engineering-protocol (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 207 tokens to every session and 266 once invoked, about $0.0008 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 2026-08-31.
Other cursor rules, from other repositories
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no-ai-coauthors
Never attribute commits to AI tools — human author only.
cursorrules
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ai-dev-os-check
Checks code changes against AI Dev OS guidelines and automatically fixes violations. Based on benchmark Test 011 — check+fix achieves +9.9 improvement vs report-only (+0.8). Supports git diff (default), staged changes, and branch comparison. Use --dry-run for report-only mode.