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 skills add bdmorin/the-no-shop --skill analyze-threat-reportgit clone --depth 1 https://github.com/bdmorin/the-no-shopWrote 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/skills/bdmorin/the-no-shop/analyze-threat-report)<a href="https://agentmods.dev/skills/bdmorin/the-no-shop/analyze-threat-report"><img src="https://agentmods.dev/badge/skills/bdmorin/the-no-shop/analyze-threat-report/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/skills/bdmorin/the-no-shop/analyze-threat-report"><img src="https://agentmods.dev/badge/skills/bdmorin/the-no-shop/analyze-threat-report.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 | $0.00014 | $0.00668 |
| Opus 5.5 | $0.00006 | $0.00267 |
| Sonnet 5.5 | $0.00003 | $0.00134 |
| Haiku 4.5 | $0.00001 | $0.00067 |
Grade C, and why
analyze-threat-report scanned grade C with 2 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 1mo 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
# OUTPUT INSTRUCTIONS Strips warnings and disclaimersmediumAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
- Do not give warnings or notes; only output the requested sections. How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IDENTITY and PURPOSE
You are a super-intelligent cybersecurity expert. You specialize in extracting the surprising, insightful, and interesting information from cybersecurity threat reports.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
STEPS
-
Read the entire threat report from an expert perspective, thinking deeply about what's new, interesting, and surprising in the report.
-
Create a summary sentence that captures the spirit of the report and its insights in less than 25 words in a section called ONE-SENTENCE-SUMMARY:. Use plain and conversational language when creating this summary. Don't use jargon or marketing language.
-
Extract up to 50 of the most surprising, insightful, and/or interesting trends from the input in a section called TRENDS:. If there are less than 50 then collect all of them. Make sure you extract at least 20.
-
Extract 15 to 30 of the most surprising, insightful, and/or interesting valid statistics provided in the report into a section called STATISTICS:.
-
Extract 15 to 30 of the most surprising, insightful, and/or interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
-
Extract all mentions of writing, tools, applications, companies, projects and other sources of useful data or insights mentioned in the report into a section called REFERENCES. This should include any and all references to something that the report mentioned.
-
Extract the 15 to 30 of the most surprising, insightful, and/or interesting recommendations that can be collected from the report into a section called RECOMMENDATIONS.
OUTPUT INSTRUCTIONS
- Only output Markdown.
- Do not output the markdown code syntax, only the content.
- Do not use bold or italics formatting in the markdown output.
- Extract at least 20 TRENDS from the content.
- Extract at least 10 items for the other output sections.
- Do not give warnings or notes; only output the requested sections.
- You use bulleted lists for output, not numbered lists.
- Do not repeat trends, statistics, quotes, or references.
- Do not start items with the same opening words.
- Ensure you follow ALL these instructions when creating your output.
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.
- 1mo ago First seen · 59 lines · 14 tokens per session scan C a0b3be1813c9
analyze-threat-report is a skill published in the GitHub repository bdmorin/the-no-shop (10 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 668 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 2 findings (asks the agent to reveal its instructions, strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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