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 skills/tykisgod/quick-question/grandmanpx skills add tykisgod/quick-question --skill grandmagit clone --depth 1 https://github.com/tykisgod/quick-questionWrote 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/tykisgod/quick-question/grandma)<a href="https://agentmods.dev/skills/tykisgod/quick-question/grandma"><img src="https://agentmods.dev/badge/skills/tykisgod/quick-question/grandma.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 | $0.00018 | $0.00392 |
| Opus 5 | $0.00009 | $0.00196 |
| Sonnet 5 | $0.00004 | $0.00078 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
grandma 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 5d 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.
What it actually says
Respond in the user's preferred language (detect from their recent messages, or fall back to the language setting in CLAUDE.md).
Explain a technical concept, module, or design decision using everyday analogies that anyone — including a grandma or a 5-year-old — could understand.
Arguments: $ARGUMENTS — any technical concept (e.g., "ECS", "why does the task system use a push model", "what is MCP", "A* pathfinding algorithm")
Behavior
- Understand the topic: If it's a project module, quickly read design docs and core code to understand what it actually does
- Find an everyday life analogy that:
- Uses a scenario everyone has experienced (cooking, queuing, moving house, school, grocery shopping...)
- Covers the core mechanism, not just a surface similarity
- If the concept has multiple layers, use different roles/stages within the SAME scenario — don't switch scenarios
- Explain the entire concept through the analogy:
- Start with the scene: "Imagine you're at..."
- Map each role and action in the scene to key parts of the technical concept
- After the analogy, "translate" back in one sentence: "What we just called X is actually Y in the code"
- If there are common misconceptions, address them: "Many people think... but actually..."
- Do NOT:
- Use technical jargon (unless the user is asking what a specific term means)
- Show code
- Say "simply put" followed by something not simple
- Say "it's like in programming..." — the audience doesn't know programming, that's not an analogy
- Be condescending ("this is basic", "you can think of it as")
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.
- 5d ago First seen · 29 lines · 18 tokens per session scan A 8649c45fbea5
grandma is a skill published in the GitHub repository tykisgod/quick-question (11 stars, last pushed 11d ago), licensed MIT. It adds 18 tokens to every session and 392 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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