An automated workflow for processing multiple open GitHub issues, the task records used to track bugs and planned work. It prioritizes issues, finds dependencies, assigns parallel agents, and checks the results.

Use it to fetch open issues, rank them by priority, identify links between them, process independent issues concurrently, and verify the outcomes.

It reduces the manual work of sorting, coordinating, and checking many GitHub issues. It also helps avoid starting dependent work in the wrong order.

skill-090 — Skill for Claude Code and Codex by legendtkl

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 legendtkl/agentic-skill-router --skill skill-090

Clone the repo

git clone --depth 1 https://github.com/legendtkl/agentic-skill-router

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-090/github.svg)](https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-090)

Your own site

<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-090"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-090/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-090"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-090.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,270 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.

Model	Per session	Once invoked
Fable 5.1	$0.00050	$0.01270
Opus 5	$0.00025	$0.00635
Sonnet 5	$0.00010	$0.00254
Haiku 4.5	$0.00005	$0.00127

Measured 7d ago against content hash 03cac7e4a7ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

skill-090 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 7d 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.

experiments/dci-compare/skillrouter-skills/skill-090/SKILL.md · 178 lines

How it starts

The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Run Issues Skill

Autonomous workflow for processing multiple GitHub issues in parallel with priority-based scheduling and verification.

Overview

This skill orchestrates the complete lifecycle of issue processing:

Fetch open issues from GitHub
Analyze and prioritize (P0 > P1 > P2)
Detect dependencies between issues
Spawn subagents for parallel execution
Verify all results before reporting

When to Use

Use this skill when:

User invokes /run-issues
User requests batch processing of issues
User wants autonomous issue handling
Multiple issues need parallel processing

Workflow

Phase 0: Pre-Flight Check

IMPORTANT: Before starting, check if AWK principal workflow is active.

# Check for active AWK workflow
if [ -f ".ai/state/kickoff.lock" ]; then
    echo "⚠️ WARNING: AWK principal workflow is active"
fi

If .ai/state/kickoff.lock exists:

Warn the user:

⚠️ AWK principal workflow 正在執行中。
同時執行 /run-issues 可能導致：
- 同一 issue 被重複處理
- 產生重複的 branch 或 PR
- Merge conflicts

建議：等待 AWK workflow 完成後再執行。
確定要繼續嗎？(yes/no)

Only proceed if user explicitly confirms with "yes"
If user says "no", abort gracefully

If lock file does not exist, proceed to Phase 1.

Phase 1: Fetch Issues

gh issue list --state open --json number,title,body,labels,assignees --limit 50

Parse the JSON output to get all open issues.

Phase 2: Analyze Issues

Read phases/analyze.md for detailed priority analysis rules.

For each issue:

Extract priority from labels (P0/P1/P2)
Parse dependencies from issue body
Calculate priority score
Build dependency graph

Phase 3: Plan Parallel Execution

Read phases/parallelize.md for parallelization strategy.

Group issues by dependency chains
Identify independent issue sets
Determine optimal subagent count (max 3 concurrent)
Create execution batches

Phase 4: Execute

For each batch of independent issues:

Read the full file on GitHub · 178 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.

7d ago First seen · 178 lines · 50 tokens per session scan A 03cac7e4a7ab

Subscribe to this mod's changes

skill-090 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 1,270 once invoked, about $0.0003 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 2026-09-03.

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