es-toolkit is a JavaScript utility library providing commonly used functions such as debouncing, delaying, chunking, summing, and selecting values, with TypeScript types and a compatibility layer for Lodash. JavaScript and TypeScript developers use it when they need utility code with small bundles and performance-focused implementations, while the catalogue skills support AI coding tools working with the library.
Borrowing it
Nothing to install: this file belongs to toss/es-toolkit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/toss/es-toolkit/main/.claude/skills/compat-review/SKILL.mdgit clone --depth 1 https://github.com/toss/es-toolkitWrote 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/toss/es-toolkit/compat-review)<a href="https://agentmods.dev/skills/toss/es-toolkit/compat-review"><img src="https://agentmods.dev/badge/skills/toss/es-toolkit/compat-review/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/toss/es-toolkit/compat-review"><img src="https://agentmods.dev/badge/skills/toss/es-toolkit/compat-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00018 | $0.00906 |
| Opus 5.5 | $0.00007 | $0.00362 |
| Sonnet 5.5 | $0.00004 | $0.00181 |
| Haiku 4.5 | $0.00002 | $0.00091 |
Grade A, and why
compat-review 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compat Layer Review
Verify that a compat PR actually fixes a real lodash inconsistency.
Input
$ARGUMENTS — PR number (e.g. 1234) or function name (e.g. chunk)
Workflow
1. Identify target function and PR claims
PR number:
gh pr view {number} --repo toss/es-toolkit --json title,body,files
From the PR description and diff, extract:
- Which compat function is being fixed
- What inconsistency the contributor claims (expected vs actual behavior)
- Any test examples the contributor provides
Function name: Read the function source and its spec to understand current behavior.
2. Build comparison test
Create a temporary vitest spec at src/compat/{category}/_compat-review-{fn}.spec.ts.
import { describe, expect, it } from 'vitest';
import { fn as compatFn } from 'es-toolkit/compat';
import { fn as lodashFn } from 'lodash';
Include two groups of test cases:
A. Contributor's claimed examples — Extract directly from the PR description or test diff. These are the cases the PR claims to fix.
B. ~10 additional edge cases you generate — Based on the function's signature and lodash's known behavior patterns:
- Empty inputs:
[],{},'',0 - Nullish:
null,undefined - Negative/zero/float numbers:
-1,0,1.5,NaN,Infinity - Type coercion: string numbers (
'3'), boolean, mixed types - Boundary: single-element arrays, very long strings, deeply nested objects
- Pick cases that are relevant to the specific function
Each test:
it('description', () => {
let lodashResult, compatResult;
let lodashErr: any, compatErr: any;
try {
lodashResult = lodashFn(args);
} catch (e) {
lodashErr = e;
}
try {
compatResult = compatFn(args);
} catch (e) {
compatErr = e;
}
if (lodashErr && compatErr) return; // both throw = consistent
if (lodashErr || compatErr) {
throw new Error(`Behavior mismatch: ${lodashErr ? 'lodash throws' : 'compat throws'}`);
}
expect(compatResult).toEqual(lodashResult);
});
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 · 135 lines · 18 tokens per session scan A c40b98be45d3
compat-review is a skill published in the GitHub repository toss/es-toolkit (11,378 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 906 once invoked, about $0.0001 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 2026-08-30.
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