gh-issues

gh-issues is a skill for Claude Code from Chemaclass/agnostic-ai. It costs 36 tokens per session (1,234 once invoked), scanned A, a copy of gh-issues, MIT.

A workflow for finding and processing open GitHub issues that are unassigned or assigned to the current user.

In plain words
What is it for?
Use it to list issues in a dry run or handle them one by one through the project’s issue-processing skill.
Why use it?
It gathers the relevant issues, removes duplicates, applies filters, and stops when an issue cannot be processed safely.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to list issues in a dry run or handle them one by one through the project’s issue-processing skill.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chemaclass/agnostic-ai/gh-issues
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.

Any agent
npx skills add Chemaclass/agnostic-ai --skill gh-issues
Clone the repo
git clone --depth 1 https://github.com/Chemaclass/agnostic-ai

Made for: Claude Code.

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 gh-issues

README.md
[![agentmods](https://agentmods.dev/badge/skills/chemaclass/agnostic-ai/gh-issues.svg)](https://agentmods.dev/skills/chemaclass/agnostic-ai/gh-issues)
Your own site
<a href="https://agentmods.dev/skills/chemaclass/agnostic-ai/gh-issues"><img src="https://agentmods.dev/badge/skills/chemaclass/agnostic-ai/gh-issues.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,234 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 86% copy Near-identical to another mod 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 5.1 $0.00036 $0.01234
Opus 5 $0.00018 $0.00617
Sonnet 5 $0.00007 $0.00247
Haiku 4.5 $0.00004 $0.00123

Measured 8d ago against content hash 1ed358367a78, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

gh-issues 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 8d 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.

Origin

This is a copy

86% identical to gh-issues — 48 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agnostic-ai/skills/gh-issues/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Issues Watcher

Purpose

Process every open GitHub issue that is unassigned or assigned to the current user (@me), one after another, by delegating each to the gh-issue skill. Stop on first hard failure so it can be inspected.

Args

  • --limit N — process at most N issues this run (default: all).
  • --label foo — only issues carrying label foo.
  • --dry-run — list issues that would be processed; do not invoke gh-issue.

Strip leading # if user passes #123 style.

Phase 1: Discover

Fetch open issues that are unassigned or assigned to @me, oldest first. GitHub search does not OR these cleanly, so run two queries and merge:

# Unassigned
gh issue list \
  --state open \
  --search "no:assignee" \
  --json number,title,labels,assignees,createdAt \
  --limit 200

# Assigned to me
gh issue list \
  --state open \
  --assignee "@me" \
  --json number,title,labels,assignees,createdAt \
  --limit 200

Merge:

  • Deduplicate by number.
  • Keep only issues whose assignees array is empty or contains the current user (gh api user -q .login).
  • Drop issues assigned to anyone else (defensive).
  • Apply --label filter if given.
  • Apply --limit if given.
  • Sort ascending by createdAt (FIFO).

Print the queue: #<num> <title> [assignee] per line, where [assignee] is unassigned or @me. If empty, exit cleanly.

Phase 2: Worktree Sanity

Before touching any issue:

git status --porcelain
git fetch origin main
git checkout main && git reset --hard origin/main

Abort if worktree dirty. Never auto-stash.

Phase 3: Process Loop

For each issue in the queue:

  1. Re-check assignment state (someone else may have grabbed it):

    gh issue view <num> --json assignees -q '.assignees[].login'
    me=$(gh api user -q .login)
    
    • Empty output → unassigned, proceed.
    • Only $me listed → already mine, proceed (skip self-assign step).
    • Any other login present → skip this issue.
  2. Invoke the gh-issue skill with the issue number. That skill owns:

    • self-assign via gh issue edit <num> --add-assignee @me (no-op if already assigned).
    • branch from fresh main (prefix from labels: fix/, feat/, docs/).
    • TDD implementation.
    • go test ./... green locally.
    • regen of derived artifacts (schema / sync / playground) when applicable.
    • changelog entry under ## [Unreleased].
    • commit with Related to #<num>.
    • mandatory final refactor pass over every touched file (separate ref(...) commit) before opening the PR.
    • PR opened with --assignee Chemaclass, matching label, Closes #<num> in body.

Read the full file on GitHub · 138 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. 8d ago First seen · 138 lines · 36 tokens per session scan A 1ed358367a78

Subscribe to this mod's changes

gh-issues is a skill published in the GitHub repository Chemaclass/agnostic-ai (11 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,234 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to gh-issues, differing in 48 lines, and is treated as a copy.

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