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 tobihagemann/turbo --skill explain-thisgit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/explain-this)<a href="https://agentmods.dev/skills/tobihagemann/turbo/explain-this"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/explain-this/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/tobihagemann/turbo/explain-this"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/explain-this.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 | $0.00102 | $0.01045 |
| Opus 5 | $0.00051 | $0.00522 |
| Sonnet 5 | $0.00020 | $0.00209 |
| Haiku 4.5 | $0.00010 | $0.00104 |
Grade A, and why
explain-this 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain This
Take whatever the user is pointing at and translate it into plain language. "This" is usually the most recent assistant output or something pasted as an argument: a multi-option prompt, a free-form question, a code block, an error, a command output, or an artifact like a plan, findings report, or diff.
Step 1: Identify the Subject
Pick the subject in priority order:
- Text passed as an argument — use that
- A quoted or selected region from the user's most recent message — use that
- The most recent non-trivial assistant output — use that
- If the guess is not obvious, lead the explanation by naming what was picked so the user can redirect
Step 2: Ground in State
Read whatever makes the explanation concrete, no more:
- Files the subject references
- The active skill's
SKILL.mdwhen a skill-specific question is being asked git statusandgit diff --statwhen the subject involves staged or unstaged changes- Any artifact cited (plan, spec, findings, test plan, audit, PR, commit)
Step 3: Produce the Explanation
The reader is an experienced developer who may not be fluent in every tech stack or acronym but doesn't need concepts from first principles. Skip ELI5. Use plain language; strip skill-internal jargon, or define it inline when the jargon is what the user needs explained (for example, "P1 peer" becomes "priority 1 finding from the peer reviewer").
Go beyond "what this does" and surface the trade-offs: pros and cons per choice, benefits and costs, whether the thing reads as clean and elegant or redundant and overcomplicated. Be honest about red flags; be honest about solid work.
Shape the output to match the subject. Use the branch that applies; drop the rest.
Question with discrete options — restate the question plainly, then enumerate options using this template:
**What you're being asked:** <plain-language restatement>
### Your Options
**1. <label as shown>** — <concrete effect: files changed, next step, what is lost>
- **Pros:** <what you gain>
- **Cons:** <what it costs>
**2. <label>** — <concrete effect>
- **Pros:** <...>
- **Cons:** <...>
### When Each Fits
- Pick **<option>** if your goal is <goal>.
- Pick **<option>** if your goal is <other goal>.
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 · 74 lines · 102 tokens per session scan A d8b95b9ac939
explain-this is a skill published in the GitHub repository tobihagemann/turbo (402 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 1,045 once invoked, about $0.0005 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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