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/issue-label/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/issue-label)<a href="https://agentmods.dev/skills/toss/es-toolkit/issue-label"><img src="https://agentmods.dev/badge/skills/toss/es-toolkit/issue-label/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/issue-label"><img src="https://agentmods.dev/badge/skills/toss/es-toolkit/issue-label.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 | $0.00013 | $0.00492 |
| Opus 5.5 | $0.00005 | $0.00197 |
| Sonnet 5.5 | $0.00003 | $0.00098 |
| Haiku 4.5 | $0.00001 | $0.00049 |
Grade A, and why
issue-label 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue Label
Analyze issue content and assign appropriate labels.
Input
$ARGUMENTS — Issue number (e.g. 1234)
Available Labels
| Label | When to use |
|---|---|
p0: major bug |
Core function broken, incorrect results, crashes |
p1: minor bug |
Edge case failures, non-critical behavior issues, type errors |
p1: docs bug |
Wrong/outdated documentation, broken links |
p2: optimization |
Performance improvements, bundle size reduction |
p2: new feature |
New function or capability request |
p2: type enhancement |
TypeScript type improvements, better generics |
p2: refactoring |
Code cleanup, internal improvements |
p2: docs enhancement |
New docs, translations, better examples |
p3: discussion |
Questions, design discussions, RFCs |
help wanted |
Good for external contributors |
Workflow
1. Fetch issue
gh issue view {number} --repo toss/es-toolkit --json title,body,labels
If labels already exist, report them and stop.
2. Analyze content
From title and body, identify:
- Is it a bug report? (error messages, "doesn't work", "incorrect", "doesn't match lodash")
- Is it a feature request? ("add", "implement", "support")
- Is it about docs? ("docs", "typo", "translation", "example")
- Is it about types? ("type", "TypeScript", "generic", "inference")
- Is it a question? (question marks, "how to", "is it possible")
3. Apply label
gh issue edit {number} --repo toss/es-toolkit --add-label "{label}"
4. Report
## Issue #{number} — {title}
### Applied Label: {label}
### Reason: {why this label fits}
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 · 65 lines · 13 tokens per session scan A 7063bed892a3
issue-label is a skill published in the GitHub repository toss/es-toolkit (11,378 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 492 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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projects
List all managed projects with status, branch, open PRs, and open issue counts — portfolio-level view.
qa-project-bootstrap
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit,"…