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 patrick-fu/awesome-skills --skill explaingit clone --depth 1 https://github.com/patrick-fu/awesome-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/patrick-fu/awesome-skills/explain)<a href="https://agentmods.dev/skills/patrick-fu/awesome-skills/explain"><img src="https://agentmods.dev/badge/skills/patrick-fu/awesome-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/patrick-fu/awesome-skills/explain"><img src="https://agentmods.dev/badge/skills/patrick-fu/awesome-skills/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 | $0.00071 | $0.00904 |
| Opus 5.5 | $0.00028 | $0.00362 |
| Sonnet 5.5 | $0.00014 | $0.00181 |
| Haiku 4.5 | $0.00007 | $0.00090 |
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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain
Scope. Apply to requested explanation, context recovery, or writing work. Ordinary implementation and its routine wrap-up remain in their existing workflow.
Route. Choose the primary outcome from the requested action and final deliverable before retrieving material. Load only the references needed for it.
| User request | Primary deliverable | Reference |
|---|---|---|
| Explain a concept, code, or current design; explain it differently | Mechanism, execution path, or example | Relevant material; usually no branch reference |
| Explain an existing PR/MR | Change illustration, verification evidence, and merge impact | Delivery |
| Write or edit PR/MR titles or bodies, issue/incident replies, or QA handoffs | Usable destination text | Delivery |
| Recover a named task or explain a historical decision | Grounded status and next action, or decision rationale | Orientation |
“Write an MR” routes to writing even when it needs background recovery or diagrams. For any scenario, read Views when a diagram, structural view, or interaction helps. These are presentation choices, not a replacement for the requested deliverable. For a bare link, use the conversation's active request; ask only if the intended action remains materially ambiguous. Review and debugging use their own workflows; Explain may support a requested explanation or writing subtask within them. When asked to resume work, follow the recovery reference through the next authorized action.
Reuse. Use supported material already in context; retrieve only facts needed for the request that are missing, stale, or conflicting.
Ground. Preserve consequential conditions. Distinguish recorded facts, mechanism-based inference, and unknowns; bound benefit and completion claims to evidence for the described artifact.
Frame. Answer first, or establish the current position when catching up. Reframe a confusing explanation with a different structure, example, or view. Apply ISO 24495-1's outcome standard: the intended reader can find, understand, and use the result. Borrow ASD-STE100's controlled-expression discipline—stable terms, direct sentence patterns, and explicit actions or conditions—without importing its English-only word list. Keep each section around one idea and match the requested depth. Prefer a compact visual beside brief prose when explaining relationships or changes; use prose alone when a visual adds no information.
Language. For each deliverable, use the user's explicitly requested language first. Otherwise follow their established language preference in the current conversation, inferring it from their own messages when unstated. In a mixed conversation without an established preference, use the language of the latest substantive user request. The language of these instructions, examples, quoted sources, code, or templates does not set the output language.
Apply the resolved language consistently to titles, body text, summaries,
headings at every level, subheadings, captions, diagram labels, and explanatory
pseudocode. Use supplied terminology and the project's GLOSSARY.md when
available. Translate ordinary explanatory terms into established domain terms
in the resolved language, without redundant foreign-language equivalents;
explain unfamiliar terms locally. Descriptive source vocabulary is prose, not
a code identifier. Keep source spelling where it identifies actual code symbols,
paths, commands, protocol fields, or proper names, adding a gloss in the resolved
language when useful.
Re-entry. When the user names ADHD or asks for low cognitive load, optimize resuming rather than simplifying away substance: foreground the current position and next action, use short labeled units, and attach conditions to the decision they constrain.
Anchor code walkthroughs in the relevant execution path.
Output. Honor explicit language and destination-format requests. Answer in chat by default; create a file when requested or required by the chosen visual medium.
What ships with it
4 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 Changed · +31 lines · +19 tokens per session 297cc186b362
- 13d ago Changed · +8 lines 380cd88fbbb2
- 15d ago First seen · 39 lines · 52 tokens per session scan A ba1376fd22d5
explain is a skill published in the GitHub repository patrick-fu/awesome-skills (69 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 904 once invoked, about $0.0003 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 2026-10-11.
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