agnostic-ai-gh-issues

agnostic-ai-gh-issues is a skill for Claude Code from Chemaclass/agnostic-ai. It costs 40 tokens per session (975 once invoked), scanned A, original, MIT.

A workflow that finds open GitHub issues that are unassigned or assigned to the current user and processes them one at a time.

In plain words
What is it for?
It helps process a backlog through the single-issue workflow, limit the number of issues, filter by label, or preview the work without changing anything.
Why use it?
It removes the need to search, combine, filter, and deduplicate issue lists manually before starting work.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit It helps process a backlog through the single-issue workflow, limit the number of issues, filter by label, or preview the work without changing anything.

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Install with agentmods
npx agentmods add skills/chemaclass/agnostic-ai/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 agnostic-ai-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 agnostic-ai-gh-issues

README.md
[![agentmods](https://agentmods.dev/badge/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues/github.svg)](https://agentmods.dev/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues)
Your own site
<a href="https://agentmods.dev/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues"><img src="https://agentmods.dev/badge/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues/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.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues"><img src="https://agentmods.dev/badge/skills/chemaclass/agnostic-ai/agnostic-ai-gh-issues.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 975 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 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 5.1 $0.00040 $0.00975
Opus 5.5 $0.00016 $0.00390
Sonnet 5.5 $0.00008 $0.00195
Haiku 4.5 $0.00004 $0.00097

Measured 6d ago against content hash 10f601a95610, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agnostic-ai-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 6d 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.

.agnostic-ai/skills/agnostic-ai-gh-issues/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 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) through the agnostic-ai-gh-issue skill. Record blockers and continue independent issues when the worktree is safe.

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 agnostic-ai-gh-issue.

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:

  • If either query returns 200 rows, repeat it with a larger --limit until the result count falls below that limit.
  • 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 (a safety check).
  • Apply --label filter if given.
  • Apply --limit if given.
  • Sort ascending by createdAt (oldest first).

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:

test -z "$(git status --porcelain)" || exit 1
git fetch origin main
git switch main
test "$(git rev-list --count origin/main..main)" -eq 0 || exit 1
git pull --ff-only

Abort if the worktree is dirty or local main is ahead of origin/main. Never auto-stash or discard local commits.

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.

Read the full file on GitHub · 102 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. 6d ago Changed 10f601a95610
  2. 10d ago First seen · 102 lines · 40 tokens per session scan A 5067e01319f7

Subscribe to this mod's changes

agnostic-ai-gh-issues is a skill published in the GitHub repository Chemaclass/agnostic-ai (25 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 975 once invoked, about $0.0002 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 2026-10-06.

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