issue-review

issue-review is a skill for Claude Code, Codex from toss/es-toolkit. It costs 15 tokens per session (587 once invoked), scanned A, original, MIT.

A tool for reviewing recent open issues, which are tracked reports or requests about a project.

In plain words
What is it for?
Use it to review issue reports, assess whether bugs or feature requests fit the project, compare them with existing behavior, and label issues.
Why use it?
It adds context to issues, checks related code and tests, and identifies possible duplicates before they are handled.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/toss/es-toolkit/issue-review
Any agent
npx skills add toss/es-toolkit --skill issue-review
Clone the repo
git clone --depth 1 https://github.com/toss/es-toolkit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for issue-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/toss/es-toolkit/issue-review.svg)](https://agentmods.dev/skills/toss/es-toolkit/issue-review)
Your own site
<a href="https://agentmods.dev/skills/toss/es-toolkit/issue-review"><img src="https://agentmods.dev/badge/skills/toss/es-toolkit/issue-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 587 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.00587
Opus 5 $0.00008 $0.00293
Sonnet 5 $0.00003 $0.00117
Haiku 4.5 $0.00002 $0.00059

Measured 4d ago against content hash 0a3e3f82e914, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issue-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 4d 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.

.claude/skills/issue-review/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Issue Review

Fetch recent issues, label unlabeled ones with context, detect duplicates.

Input

$ARGUMENTS — Number of issues (default: 10)

Examples:

  • /issue-review — 10 most recent open issues
  • /issue-review 20 — 20 issues

Workflow

1. Fetch recent issues

gh issue list --repo toss/es-toolkit --state open --limit {count} --json number,title,author,labels,createdAt

2. Deep review per issue

For each issue:

a. Read issue content
gh issue view {number} --repo toss/es-toolkit --json title,body,labels,comments
b. Read related source code

If the issue mentions a specific function:

  • Read the function source to understand current behavior
  • Read existing tests to see what's covered
  • Check if there's already a compat variant
c. Provide context
  • Bug reports: Is the reported behavior actually a bug? Or is it by design? Does lodash behave differently?
  • Feature requests: Does this align with design principles? Is it replaceable by modern JS? Is it TC39 Stage 3+?
  • Type issues: Read the current type signature, assess the proposed change
  • Docs: Check what's currently documented vs what's being requested
d. Label if unlabeled

If no labels exist, run /issue-label {number}.

3. Detect duplicates

gh issue list --repo toss/es-toolkit --state all --search "{function name}" --limit 10 --json number,title,state,labels

Group by:

  • Same function name in title
  • Similar error descriptions
  • Same feature being requested

4. Report per issue

### Issue #{number} — {title}

**Label**: {existing or newly applied}
**Context**: {what the function currently does, relevant code snippet}
**Analysis**: {is the request valid? design principle alignment?}
**Duplicates**: {similar issues if any}
**Action**: {label applied / needs discussion / close as wontfix / link to existing PR}

5. Summary

## Issue Review — {date}

| # | Title | Label | Duplicate? | Action |
|---|-------|-------|------------|--------|

- {N} issues reviewed
- {N} newly labeled
- {N} potential duplicates
- {N} actionable bugs
- {N} feature requests

Read the full file on GitHub · 96 lines

Changes

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.

  1. 4d ago First seen · 96 lines · 15 tokens per session scan A 0a3e3f82e914

Subscribe to this mod's changes

issue-review is a skill published in the GitHub repository toss/es-toolkit (11,329 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 587 once invoked, about $0.0001 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 2026-08-30.

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