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 LerianStudio/ring --skill engineering-promptsgit clone --depth 1 https://github.com/LerianStudio/ringWrote 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/lerianstudio/ring/engineering-prompts)<a href="https://agentmods.dev/skills/lerianstudio/ring/engineering-prompts"><img src="https://agentmods.dev/badge/skills/lerianstudio/ring/engineering-prompts/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/lerianstudio/ring/engineering-prompts"><img src="https://agentmods.dev/badge/skills/lerianstudio/ring/engineering-prompts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 56 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00074 | $0.01083 |
| Opus 5.5 | $0.00030 | $0.00433 |
| Sonnet 5.5 | $0.00015 | $0.00217 |
| Haiku 4.5 | $0.00007 | $0.00108 |
Grade B, and why
ring:engineering-prompts scanned grade B with 1 finding 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.
1. **Display Prompt**: Show complete prompt text in formatted code block How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering Prompts
When to use
- Crafting new prompts for LLM-based systems or AI assistants
- Optimizing existing prompts that underperform or produce inconsistent results
- Selecting appropriate prompting techniques for a specific use case
- Structuring complex multi-step reasoning prompts
Skip when
- The prompt is trivial and already producing good results
- The task is a direct code change, not prompt creation
- You need to execute the task described in the prompt rather than create a prompt for it
Scope Boundaries
THIS SKILL ONLY GENERATES PROMPTS. IT NEVER:
- Proactively explores, modifies, or debugs any files in the codebase
- Attempts to fix, debug, or improve code in the project
- Performs the task described in the user's input
Allowed reads: Files the user explicitly references as input context, and docs/prompts/ for saving output.
THE INPUT IS A DESCRIPTION OF WHAT THE PROMPT SHOULD DO, NOT A TASK TO PERFORM.
Example: Help debug React performance issues means:
- CREATE a prompt that helps users debug React performance issues
- DO NOT actually debug any React code
Process
Phase 1: Input Analysis
- Parse Input: Analyze the provided description or file content
- Identify Use Case: Determine the intended application and requirements
- Select Techniques: Choose appropriate prompting patterns and methods
Phase 2: Prompt Construction
- Structure Design: Create clear prompt architecture using proven patterns
- Technique Application: Apply selected prompting techniques (few-shot, chain-of-thought, etc.)
- Constraint Setting: Define boundaries and output format specifications
- Validation: Ensure prompt follows best practices and guidelines
Phase 3: Documentation & Delivery
- Display Prompt: Show complete prompt text in formatted code block
- Implementation Notes: Explain techniques used and design rationale
- Usage Guidelines: Provide clear instructions for implementation
- Performance Tips: Include optimization suggestions and best practices
- Save Output: Save the generated prompt to
docs/prompts/directory (create if needed)
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 · 146 lines · 74 tokens per session scan B e6de2537ae3e
ring:engineering-prompts is a skill published in the GitHub repository LerianStudio/ring (218 stars, last pushed 3d ago), licensed Apache-2.0. It adds 74 tokens to every session and 1,083 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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