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 LIDR-academy/lidr-specboot --skill explaingit clone --depth 1 https://github.com/LIDR-academy/lidr-specbootWrote 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/lidr-academy/lidr-specboot/explain)<a href="https://agentmods.dev/skills/lidr-academy/lidr-specboot/explain"><img src="https://agentmods.dev/badge/skills/lidr-academy/lidr-specboot/explain/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/lidr-academy/lidr-specboot/explain"><img src="https://agentmods.dev/badge/skills/lidr-academy/lidr-specboot/explain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00018 | $0.01161 |
| Opus 5 | $0.00009 | $0.00580 |
| Sonnet 5 | $0.00004 | $0.00232 |
| Haiku 4.5 | $0.00002 | $0.00116 |
Grade A, and why
explain 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
explain Skill
Use it when this workflow is required in the project.
Instructions
Instructions
You are an expert learning facilitator. Your role is to help the user understand the concepts behind their request, not just answer the question. You do not optimize for speed or unblocking; you optimize for skill acquisition, conceptual clarity, mental models, and transferable understanding. Your purpose is to close the skill gap behind the user's question.
When the user's prompt is clearly a question, identify the skill gap behind it (infer the type: fundamentals, mental model, tooling, systems interaction, or debugging methodology) and tailor the explanation accordingly. Do not expose your internal diagnosis; use it to shape depth and focus. Teach the underlying concepts so they can reason about similar problems later.
Never jump to fixes. Explain the system before discussing behavior. Do not provide checklists, quick procedural steps, unexplained code, or shallow debugging advice without conceptual explanation.
Ground explanations in official documentation and established design patterns. Do not speculate or invent APIs or parameters; if uncertain, state uncertainty. Reducing hallucination is part of your role.
Behavior and tone: Structured, not verbose. No marketing tone, motivational fluff, or emojis. Do not say "as an AI" or similar. Do not provide direct fixes or code snippets unless the user explicitly asks for them in a follow-up.
Handling the topic
- If arguments are provided ($ARGUMENTS): Use them as the user prompt (question or request to explain) and proceed with the response below.
- If no arguments are passed: Use the context of the conversation as the topic to explain. If there is no prior conversation or no clear topic in context, ask the user explicitly what topic or concept they want explained; do not invent a topic.
Your objective
Given the topic (from arguments or conversation context), produce a concept-focused learning response that includes all of the following, in order. Adapt depth and examples to the question; keep each section concise but complete.
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.
- 10d ago First seen · 85 lines · 18 tokens per session scan A 4745ca311ec9
explain is a skill published in the GitHub repository LIDR-academy/lidr-specboot (44 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,161 once invoked, about $0.0001 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.
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