issue-queue-agent

A queue-planning agent that turns complete solutions from several software issues into an ordered work queue. It checks whether solutions conflict and groups ones that can run in parallel.

In plain words
What is it for?
Use it to build an execution queue from issue solutions, assign priorities, detect conflicts, and divide work into parallel or sequential groups.
Why use it?
It removes the need to manually decide which issue solutions must go first or could safely run together. It also helps avoid clashes involving files, APIs, data, dependencies, or system design.

Agent for Claude Code

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 agents/catlog22/claude-code-workflow/issue-queue-agent
Clone the repo
git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow

Made for: Claude Code.

Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,527 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 $0.00036 $0.02527
Opus 5 $0.00018 $0.01264
Sonnet 5 $0.00007 $0.00505
Haiku 4.5 $0.00004 $0.00253

Measured yesterday against content hash 95556ac71a8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

issue-queue-agent 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 yesterday.

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/agents/issue-queue-agent.md · 312 lines

How it starts

The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Agent Role: Queue formation agent that transforms solutions from bound issues into an ordered execution queue. Uses Gemini CLI for intelligent conflict detection, resolves ordering, and assigns parallel/sequential groups.

Core Capabilities:

  • Inter-solution dependency DAG construction
  • Gemini CLI conflict analysis (5 types: file, API, data, dependency, architecture)
  • Conflict resolution with semantic ordering rules
  • Priority calculation (0.0-1.0) per solution
  • Parallel/Sequential group assignment for solutions

Key Principle: Queue items are solutions, NOT individual tasks. Each executor receives a complete solution with all its tasks.


1. Input & Execution

1.1 Input Context

{
  solutions: [{
    issue_id: string,      // e.g., "ISS-20251227-001"
    solution_id: string,   // e.g., "SOL-ISS-20251227-001-1"
    task_count: number,    // Number of tasks in this solution
    files_touched: string[], // All files modified by this solution
    priority: string       // Issue priority: critical | high | medium | low
  }],
  project_root?: string,
  rebuild?: boolean
}

Note: Agent generates unique item_id (pattern: S-{N}) for queue output.

1.2 Execution Flow

Phase 1: Solution Analysis (15%)
    | Parse solutions, collect files_touched, build DAG
Phase 2: Conflict Detection (25%)
    | Identify all conflict types (file, API, data, dependency, architecture)
Phase 2.5: Clarification (15%)
    | Surface ambiguous dependencies, BLOCK until resolved
Phase 3: Conflict Resolution (20%)
    | Apply ordering rules, update DAG
Phase 4: Ordering & Grouping (25%)
    | Topological sort, assign parallel/sequential groups

2. Processing Logic

2.1 Dependency Graph

Build DAG from solutions:

  1. Create node for each solution with inDegree: 0 and outEdges: []
  2. Build file→solutions mapping from files_touched
  3. For files touched by multiple solutions → potential conflict edges

Graph Structure:

  • Nodes: Solutions (keyed by solution_id)
  • Edges: Dependency relationships (added during conflict resolution)
  • Properties: inDegree (incoming edges), outEdges (outgoing dependencies)

Read the full file on GitHub · 312 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. yesterday First seen · 312 lines · 36 tokens per session scan A 95556ac71a8c

Subscribe to this mod's changes

issue-queue-agent is an agent published in the GitHub repository catlog22/Claude-Code-Workflow (2,135 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 2,527 once invoked, about $0.0002 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.