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 shubham0704/claude-skills --skill explain-systems-visuallygit clone --depth 1 https://github.com/shubham0704/claude-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/shubham0704/claude-skills/explain-systems-visually)<a href="https://agentmods.dev/skills/shubham0704/claude-skills/explain-systems-visually"><img src="https://agentmods.dev/badge/skills/shubham0704/claude-skills/explain-systems-visually/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/shubham0704/claude-skills/explain-systems-visually"><img src="https://agentmods.dev/badge/skills/shubham0704/claude-skills/explain-systems-visually.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00059 | $0.01654 |
| Opus 5.5 | $0.00024 | $0.00662 |
| Sonnet 5.5 | $0.00012 | $0.00331 |
| Haiku 4.5 | $0.00006 | $0.00165 |
Grade A, and why
explain-systems-visually 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 17d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain Systems Visually
Teach why each object is needed, what it means, and how it advances the opening question. A readable diagram and a defined symbol do not establish understanding. Preserve the overall map while revealing each operation and its consequences.
Respect the requested medium, audience, and duration. A teaching walkthrough and a short research talk need different depth; do not turn every request into a deck or add slides automatically. Retain an equation-and-text format when requested.
Establish the teaching contract
Read the current source and implementation before explaining them. Retain their notation and abstraction boundaries; identify source disagreements instead of silently combining versions. Separate supplied method, implementation choices, proposed extensions, and demonstrated results.
State the audience's starting knowledge and one question the explanation should enable them to answer. Put the intended output or decision near the beginning, before its machinery. If audience or duration is missing, state a reasonable assumption; ask only when the answer would materially change the artifact.
For each meaningful block, establish its role, input, operation, output, persistent state, initialization, and parameters. Mark quantities as supplied, measured, inferred, learned, solved, or predicted, as applicable at each phase. An observed quantity in training may be predicted during deployment. A learned function, integrator, state, and coordinate transform are different objects. Keep this contract in authoring notes, not as boilerplate on every slide.
Plan progression before layout
For a new sequence or a flow repair, read references/learning-flow.md. Check three scales:
- Whole explanation: purpose, dependencies, method, consequence, evidence.
- Within each section: establish the need, teach the operation, use its result.
- Adjacent slides or reveals: the next step consumes something already understood.
What ships with it
5 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.
- 17d ago First seen · 153 lines · 59 tokens per session scan A e07768e7ed41
explain-systems-visually is a skill published in the GitHub repository shubham0704/claude-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 59 tokens to every session and 1,654 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-01.
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