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.
git clone --depth 1 https://github.com/latestaiagents/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/commands/latestaiagents/agent-skills/explain-code)<a href="https://agentmods.dev/commands/latestaiagents/agent-skills/explain-code"><img src="https://agentmods.dev/badge/commands/latestaiagents/agent-skills/explain-code/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/commands/latestaiagents/agent-skills/explain-code"><img src="https://agentmods.dev/badge/commands/latestaiagents/agent-skills/explain-code.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 | $0.00007 | $0.01065 |
| Opus 5.5 | $0.00003 | $0.00426 |
| Sonnet 5.5 | $0.00001 | $0.00213 |
| Haiku 4.5 | $0.00001 | $0.00106 |
Grade A, and why
explain-code 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 1mo 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/explain-code
Generate clear explanations for complex code sections.
What to Explain
Share the code you want explained, or point me to a file.
You can ask for:
- Overview - What does this code do at a high level?
- Line-by-line - Explain each part in detail
- Concept - Explain the underlying pattern or algorithm
- Why - Explain design decisions and tradeoffs
Explanation Levels
Level 1: Quick Summary
One paragraph explaining what the code does:
This function implements a debounce mechanism that delays executing
a callback until after a specified wait time has passed since the
last invocation. It's commonly used to limit the rate of API calls
triggered by user input like typing in a search box.
Level 2: Annotated Code
Comments explaining each significant line:
function debounce<T extends (...args: any[]) => any>(
func: T, // The function to debounce
wait: number // Milliseconds to wait
): (...args: Parameters<T>) => void {
let timeoutId: NodeJS.Timeout | null = null; // Store timeout reference
return (...args: Parameters<T>) => {
// Clear any existing timeout (reset the timer)
if (timeoutId) {
clearTimeout(timeoutId);
}
// Set new timeout - func will only run if no new calls come in
timeoutId = setTimeout(() => {
func(...args); // Call original function with arguments
timeoutId = null; // Clean up reference
}, wait);
};
}
Level 3: Concept Deep Dive
Explain the underlying pattern:
## Debouncing Explained
**Problem:** User types in search box, triggering API call on every keystroke.
Typing "hello" causes 5 API calls (h, he, hel, hell, hello).
**Solution:** Debouncing waits until user stops typing before making the call.
Only 1 API call for "hello" (after 300ms of no typing).
**How it works:**
1. User types 'h' → Start 300ms timer
2. User types 'e' (100ms later) → Cancel timer, start new 300ms timer
3. User types 'l' (100ms later) → Cancel timer, start new 300ms timer
4. ... continues until user stops
5. 300ms passes with no typing → Execute API call with "hello"
**Visual timeline:**
Keystrokes: h----e----l----l----o-------------------> Timers: [==X] [==X] [==X] [==X] [=====EXECUTE!] └── 300ms pause
**Related concepts:**
- **Throttling:** Execute at most once per interval (different from debounce)
- **Leading edge:** Execute immediately, then debounce subsequent calls
- **Trailing edge:** (default) Execute after the wait period
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.
- 1mo ago First seen · 143 lines · 7 tokens per session scan A 2c63f090eab5
explain-code is a command published in the GitHub repository latestaiagents/agent-skills (6 stars, last pushed 6mo ago), licensed MIT. It adds 7 tokens to every session and 1,065 once invoked, about $0.0000 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 2026-08-31.
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