Borrowing it
Nothing to install: this file belongs to ieeecsopen/mcp-cs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ieeecsopen/mcp-cs/main/.agents/skills/ai-prompt-evaluator/SKILL.mdgit clone --depth 1 https://github.com/ieeecsopen/mcp-csWrote 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/ieeecsopen/mcp-cs/ai-prompt-evaluator)<a href="https://agentmods.dev/skills/ieeecsopen/mcp-cs/ai-prompt-evaluator"><img src="https://agentmods.dev/badge/skills/ieeecsopen/mcp-cs/ai-prompt-evaluator/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/ieeecsopen/mcp-cs/ai-prompt-evaluator"><img src="https://agentmods.dev/badge/skills/ieeecsopen/mcp-cs/ai-prompt-evaluator.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 | $0.00109 | $0.00662 |
| Opus 5 | $0.00055 | $0.00331 |
| Sonnet 5 | $0.00022 | $0.00132 |
| Haiku 4.5 | $0.00011 | $0.00066 |
Grade B, and why
ai-prompt-evaluator scanned grade B 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 11d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
Design robust, deterministic, and injection-resistant system prompts for AI agents and LLM applications. Poorly structured prompts suffer from instruction drift, role confusion, hallucinations under ambiguous inputs, and Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Asks the agent to reveal its instructionslowSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
description: Activate when designing, evaluating, red-teaming, and refining LLM system prompts, agent instructions, structured JSON schemas, and defense boundaries against prompt injections and hallucinations — trigger p Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
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.
- 11d ago First seen · 62 lines · 109 tokens per session scan B fe0fa957001a
ai-prompt-evaluator is a skill published in the GitHub repository ieeecsopen/mcp-cs (3 stars, last pushed 7d ago), with no licence file. It adds 109 tokens to every session and 662 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 2 findings (instruction-override phrasing, asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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