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/mhaggis/security-detections-mcp/contentctl-pathgit clone --depth 1 https://github.com/MHaggis/Security-Detections-MCPWrote 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/mhaggis/security-detections-mcp/contentctl-path)<a href="https://agentmods.dev/rules/mhaggis/security-detections-mcp/contentctl-path"><img src="https://agentmods.dev/badge/rules/mhaggis/security-detections-mcp/contentctl-path.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 5.1 | $0.00611 | $0.00611 |
| Opus 5 | $0.00305 | $0.00305 |
| Sonnet 5 | $0.00122 | $0.00122 |
| Haiku 4.5 | $0.00061 | $0.00061 |
Grade A, and why
contentctl-path 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 6d 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
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 6d ago First seen · 84 lines · 611 tokens per session scan A b1ca5f0dcc08
contentctl-path is a cursor rule published in the GitHub repository MHaggis/Security-Detections-MCP (483 stars, last pushed 2mo ago), with no licence file. It adds 611 tokens to every session, about $0.0031 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
agent-config-test-confirmation
Require explicit user approval before running or creating tests that mutate active agent configs.
langchain-workflow-provider-agnostic
Langchain workflow changes must work regardless of model/provider choice.
ui-designer
UI designer rules — theme variables, color usage, no literal hex in app code.
fail-closed-verification
Fail-closed verification protocol — direct validation required; no speculation; mutable data/config protected.
pytest-run-tests-integration
All pytest tests for ongoing use must be runnable via runtests.py.
lg-workflow
When the user says lg or LG, you must run the full workflow yourself from hygiene through push to the current branch. Do not stop at commit or ask the user to push manually.