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 LFTPadilla/agent-dev-kit --skill explain-conceptgit clone --depth 1 https://github.com/LFTPadilla/agent-dev-kitWrote 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/lftpadilla/agent-dev-kit/explain-concept)<a href="https://agentmods.dev/skills/lftpadilla/agent-dev-kit/explain-concept"><img src="https://agentmods.dev/badge/skills/lftpadilla/agent-dev-kit/explain-concept/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/lftpadilla/agent-dev-kit/explain-concept"><img src="https://agentmods.dev/badge/skills/lftpadilla/agent-dev-kit/explain-concept.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 | $0.00107 | $0.00689 |
| Opus 5 | $0.00053 | $0.00345 |
| Sonnet 5 | $0.00021 | $0.00138 |
| Haiku 4.5 | $0.00011 | $0.00069 |
Grade A, and why
explain-concept 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 today.
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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain Concept 🧭
Umbrella router. It does not render anything. It picks the medium, hands off to one skill, and records what was learned.
When to use
- A request names an audience but not a format ("help the team understand the retry logic").
- A ticket, a bug, or a design must be explained to somebody who did not write it.
- You are about to write three paragraphs of prose about a structure. Stop and route.
Do not use it when the user already named the medium. Call that skill directly.
Step 1 — Clarify in ONE question
Ask one question only, and only if the answer is not already obvious:
Who is this for, and how will they receive it (image, editable file, or video)?
If the request already names an audience and a medium, skip the question.
Step 2 — Route
| Signal in the request | Route to | Output |
|---|---|---|
| Quick topology, flow, or architecture picture; paste into chat or a PR | diagram-render |
PNG |
| The reader must edit it, restyle it, or export SVG/PDF; swimlanes, UML, ER | drawio-skill |
.drawio + export |
| Narrated walkthrough, async share, non-technical audience, onboarding | explainer-video |
videos/<slug>/renders/video.mp4 |
| No image is possible or wanted; the reader will read the code | text trail | ordered file:line list |
Rules for the routes:
- diagram-render — the picture is static and the reader only looks at it.
- drawio-skill — the picture has a second life: somebody changes it later.
- explainer-video — timing matters. The reader needs the order of events spoken, not inferred. Example: a webhook race bug where two handlers write the same row.
- text trail — the fallback. Give an ordered list of
file:linestops, one sentence per stop on what to notice, and 5 lines of summary at most. Do not paraphrase the code.
Pick one route. Do not produce two mediums for the same request unless the user asks for both.
Step 3 — Always record lessons
After the chosen skill finishes, append one line to that skill's
references/lessons.md if anything was learned:
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.
- today First seen · 63 lines · 107 tokens per session scan A b056a519b7b5
explain-concept is a skill published in the GitHub repository LFTPadilla/agent-dev-kit (2 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 689 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 2026-09-12.
Other skills, from other repositories
lookup-topic
Look up a help topic with progressive depth. First call returns concept, repeat calls escalate to task then reference. Triggers on: look up topic, open template, tell me more, go deeper, start over.
lookup
Look up help topics with progressive depth. Pair with attune-ai for the full author-and-read workflow. Triggers on: lookup, look up, depth, topic, help topic, tell me more.
lookup-list
List all available help topics, optionally filtered by tag. Use to browse what's in the bundled templates or the project's .help/ directory. Triggers on: list topics, what's available, browse help, show topics.
lookup-warn
Get context warnings for a file based on its extension and name. Surfaces known gotchas before the user hits them. Triggers on: warn me, gotchas, pitfalls, what should I watch out for, check this file.
axiom-apple-docs-research
Use when researching Apple frameworks, APIs, or WWDC sessions - provides techniques for retrieving full transcripts, code samples, and documentation using Chrome browser and sosumi.ai.
learn
Learn a tech topic to a correct 101 level in minimal time. Researches open sources (official docs/releases, engineering blogs, YouTube talks, HN/Reddit, news, papers) restricted to recent material, then produces a brief with a 101 mental model, what changed, tradeoffs, an adopt/trial/hold/avoid verdict, a…