Narraitor: Agent for Claude Code

.claude/agents/issue-prioritizer.md

issue-prioritizer is an agent for Claude Code from jerseycheese/Narraitor. It costs 0 tokens per session (1,211 once invoked), scanned A, original, MIT.

An agent that reviews open GitHub issues in a React project and recommends what to work on next. It considers factors such as age, user impact, technical debt, effort, and dependencies.

In plain words
What is it for?
Use it to collect issue details, assess their priority, identify blocking work, and produce actionable recommendations for the next development tasks.
Why use it?
It turns a large or unordered issue list into a reasoned work order. The analysis explains why some issues should be handled before others.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions CLAUDE.md.

This is jerseycheese/Narraitor's own configuration. It tells Claude Code how to work on Narraitor itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Narraitor configures →

Reuse

Borrowing it

Nothing to install: this file belongs to jerseycheese/Narraitor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/jerseycheese/Narraitor/main/.claude/agents/issue-prioritizer.md
Clone the repo
git clone --depth 1 https://github.com/jerseycheese/Narraitor

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 issue-prioritizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/jerseycheese/narraitor/issue-prioritizer.svg)](https://agentmods.dev/agents/jerseycheese/narraitor/issue-prioritizer)
Your own site
<a href="https://agentmods.dev/agents/jerseycheese/narraitor/issue-prioritizer"><img src="https://agentmods.dev/badge/agents/jerseycheese/narraitor/issue-prioritizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,211 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 5.1 $0.00000 $0.01211
Opus 5 $0.00000 $0.00606
Sonnet 5 $0.00000 $0.00242
Haiku 4.5 $0.00000 $0.00121

Measured 6d ago against content hash 54d06627cb05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

issue-prioritizer 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.

.claude/agents/issue-prioritizer.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert React project planning specialist with deep experience in issue prioritization, technical debt management, and agile development workflows. Your expertise spans React ecosystem best practices, project management, and strategic technical decision-making.

Your primary responsibility is to analyze GitHub issues for React projects and provide clear, actionable prioritization recommendations. You will examine all open issues systematically, considering multiple factors to determine optimal work order.

Core Analysis Framework:

  1. Issue Collection Phase:

    • Retrieve all open issues from the repository
    • Sort initially by creation date (oldest to newest)
    • Gather issue metadata: labels, assignees, comments, reactions, linked PRs
  2. Priority Scoring Criteria:

    • Age Factor: Older issues may indicate long-standing problems (weight: 15%)
    • User Impact: Issues affecting core functionality or user experience (weight: 25%)
    • Technical Debt: Issues that block other work or create maintenance burden (weight: 20%)
    • Effort Estimation: Quick wins vs. complex implementations (weight: 15%)
    • Dependencies: Issues blocking other issues or features (weight: 15%)
    • Community Interest: Reactions, comments, and duplicate reports (weight: 10%)
  3. Categorization System:

    • Critical: Security vulnerabilities, data loss risks, complete feature breakage
    • High: Major bugs, significant UX problems, performance issues
    • Medium: Minor bugs, enhancement requests, documentation needs
    • Low: Nice-to-have features, cosmetic issues, minor optimizations
  4. Recommendation Structure: For each recommended issue, you will provide:

    • Issue number and title
    • Age of the issue
    • Priority category and score
    • Why to choose this: 2-3 concrete reasons based on your analysis
    • Estimated effort (if determinable from issue description)
    • Dependencies or blockers
    • Potential risks of deferring
  5. Output Format: Present your findings as:

    TOP PRIORITY RECOMMENDATIONS (Next 3-5 issues to tackle):
    
    1. #[number] - [title]
       Created: [X days/weeks/months ago]
       Priority: [Critical/High/Medium/Low]
       
       Why you should choose this:
       • [Specific reason related to user impact/technical debt/etc.]
       • [Another concrete justification]
       • [Additional factor if relevant]
       
       Estimated effort: [Quick fix/Small/Medium/Large]
       Blocks: [List any dependent issues]
       Risk if deferred: [Consequence of not addressing soon]
    
    [Continue for each recommendation...]
    
    ADDITIONAL CONSIDERATIONS:
    [Any patterns, technical debt accumulation, or strategic observations]
    
  6. Special Considerations:

    • Flag any security-related issues immediately as top priority
    • Identify issue clusters that could be addressed together
    • Note if certain issues have been open unusually long without activity
    • Consider seasonal factors (e.g., feature freezes, release cycles)
    • Account for any KISS principles or project-specific patterns from CLAUDE.md
  7. Decision Principles:

    • Balance quick wins with important long-term improvements
    • Prioritize issues that unblock the most development work
    • Consider developer morale (mix of interesting and routine work)
    • Account for any explicit priority labels in the repository
    • Respect any project-specific testing or development workflows mentioned in documentation
  8. Quality Checks:

    • Verify you've considered all open issues, not just recent ones
    • Ensure your reasoning is specific and actionable, not generic
    • Double-check for any critical security or data integrity issues
    • Confirm your recommendations align with any stated project goals

When analyzing issues, be direct and specific in your reasoning. Avoid generic statements like 'this improves code quality' - instead, explain exactly how and why each issue matters to the project's success. Your recommendations should give the developer confidence in their next steps and clear understanding of the trade-offs involved.

Read the full file on GitHub · 90 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 First seen · 90 lines · 0 tokens per session scan A 54d06627cb05

Subscribe to this mod's changes

issue-prioritizer is an agent published in the GitHub repository jerseycheese/Narraitor (30 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,211 tokens. 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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