Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add melodic-software/claude-code-plugins/plugin install educationWrote 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/melodic-software/claude-code-plugins/explain)<a href="https://agentmods.dev/skills/melodic-software/claude-code-plugins/explain"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/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/melodic-software/claude-code-plugins/explain"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/explain.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 | $0.00124 | $0.02135 |
| Opus 5.5 | $0.00050 | $0.00854 |
| Sonnet 5.5 | $0.00025 | $0.00427 |
| Haiku 4.5 | $0.00012 | $0.00214 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain it in plain words
Explain one thing, once, at the lowest useful altitude, then climb only when the reader asks. The method is the Feynman technique. When a plain inline answer already lands, just answer.
The core move
-
Identify the object. The argument, or with none, the previous assistant response (Empty argument). Done when you can name the object in one sentence, or, on a cold start with no prior assistant message, have asked what to explain instead of guessing.
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Ground it, don't recall it. Re-read the actual artifact this turn (the message, the file, the error text, the code). For an external concept, fetch a primary source. Done when the explanation cites a specific passage, file, error text or fetched source re-read this turn. A recalled paraphrase does not count.
For a subsystem of the current codebase, when the discovery skills are available, invoke
/discovery:explore --output explain <subsystem>for what the code does and/discovery:trace-intent <subsystem>for why it was built that way, and explain from what they return. Keep trace-intent's confidence wording: a reason it marked inferred stays hedged ("appears to", "likely"), and one it could not find stays "not found", in plain words. Without those skills, read the files yourself and cite them; state a reason for a design choice only when a file you read gives it. -
Land at the starting rung (Starting rung). Rung 1 (
plain) is brief and rests on one everyday analogy, with no jargon and no term that presumes background; an unavoidable technical word gets an ordinary-words gloss where it first appears. Lead with the analogy and "what it's actually doing", not vocabulary. Rung 3 (peer) opens with an exact definition in the field's own terms, then works the user's example through it without loosening it. Done when a rung 1 answer has an analogy whose parts map to the object's, a "what it's actually doing" line and no unglossed term, and a rung 3 answer opens with the exact definition. -
Close with the handoff line, then the starting-rung report line. Done when the reply ends with that single handoff line followed by the starting-rung report line.
What ships with it
6 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.
- 5d ago Changed · -56 lines · -97 tokens per session 3c91a7d5aa60
- 8d ago Changed · +61 lines aa2ea4e75449
- 16d ago Changed · -1 lines 787b4e78e97f
- 17d ago Changed · +7 lines 3fa2aead5983
- 1mo ago First seen · 140 lines · 221 tokens per session scan A 4bf27fc951ca
explain is a skill published in the GitHub repository melodic-software/claude-code-plugins (26 stars, last pushed today), licensed MIT. It adds 124 tokens to every session and 2,135 once invoked, about $0.0005 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 2026-09-03.
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Career goal mapping with skill gap analysis, actionable development plans, and milestone tracking. Use when planning career transitions, identifying skill gaps, setting professional development goals, or evaluating career options.
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parallel-orchestrator
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parallel-worker
Execute focused implementation tasks in a parallel workflow. Use when: working on assigned files in a worktree, making checkpoint commits, signaling dependencies or blockers, completing orchestrator-assigned tasks. Triggers: worker, checkpoint, worktree, assigned scope, commit prefix, parallel task.