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 hugobowne/show-us-your-agent-skills --skill explaingit clone --depth 1 https://github.com/hugobowne/show-us-your-agent-skillsWrote 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/hugobowne/show-us-your-agent-skills/explain)<a href="https://agentmods.dev/skills/hugobowne/show-us-your-agent-skills/explain"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/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/hugobowne/show-us-your-agent-skills/explain"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/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 | $0.00048 | $0.00724 |
| Opus 5 | $0.00024 | $0.00362 |
| Sonnet 5 | $0.00010 | $0.00145 |
| Haiku 4.5 | $0.00005 | $0.00072 |
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 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.
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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain: Conceptual Clarity Over Mechanical Completeness
When the user asks you to explain changes, review what's on a branch, walk through the codebase, or understand how something works, use this approach.
The Style
Conceptual clarity over mechanical completeness. Lead with the mental model, then layer in specifics that illuminate it. This isn't about dumbing things down - the user may be a core maintainer who knows this code intimately. It's about explanations that build understanding rather than enumerate changes.
Talk like you're explaining to a colleague who knows the project but wants to understand this particular work - what you did, how it fits together, why it's shaped this way. Conversational, not documentary. Express enthusiasm when something is elegant. Invite follow-up. Don't quote ADR language or doc-speak - say it how you'd actually say it.
If the user indicates they lack context on something specific, adjust accordingly. But default to assuming expertise.
What NOT To Do
- No itemized lists of changes
- No file-by-file summaries
- No mechanical descriptions of what was modified
- No changelog-style output
These are useless for understanding.
What To Do
Provide a guided tour that builds understanding.
Structure Your Explanation
-
Lead with the conceptual model: What is this system trying to do? What are the key abstractions? How do they relate to each other?
-
The formal behavior: How does the system work now? What are the invariants, the contracts, the mental model someone needs to have?
-
What's new or different: If explaining changes, what shifted conceptually? Not "added function X" but "we now support Y, which means Z."
-
What this enables: Developer-facing implications. What can someone do now that they couldn't before? What patterns does this unlock?
-
What we're teeing up: If this is setting up for future work, say so. Help the user see the trajectory.
Depth
Err on the side of thoroughness. A rich explanation that builds complete understanding is better than a crisp summary that leaves gaps. Walk through how things actually work - show the flow, explain the mechanics, make the runtime behavior clear. The user can always ask you to trim; they can't fill in what you left out.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 64 lines · 48 tokens per session scan A a376c57da921
explain is a skill published in the GitHub repository hugobowne/show-us-your-agent-skills (67 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 724 once invoked, about $0.0002 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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