junie

A skill for delegating coding tasks or requesting a second opinion from the Junie command-line tool. It chooses between delegation and validation based on the request and checks which models are available.

In plain words
What is it for?
Offloading coding tasks, cross-checking code, validating plans, and getting another view of an architecture decision through Junie CLI.
Why use it?
It lets you send work or plans to another coding agent when you want extra implementation help or an independent review.

Skill for Claude CodeCodex

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 skills/darshitpp/x-agent/junie
Any agent
npx skills add darshitpp/x-agent --skill junie
Clone the repo
git clone --depth 1 https://github.com/darshitpp/x-agent

Made for: Claude Code, Codex.

Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 244 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 $0.00083 $0.00244
Opus 5 $0.00042 $0.00122
Sonnet 5 $0.00017 $0.00049
Haiku 4.5 $0.00008 $0.00024

Measured 2d ago against content hash 29e4499a1e46, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

junie 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 2d 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.

junie/SKILL.md · 28 lines

What it actually says

Cross-Agent Task Runner — Junie CLI

Procedures

Step 1: Self-Call Detection

  1. Check for JUNIE_SESSION or JetBrains-specific environment markers.
  2. If detected, stop and inform the user: "Cannot invoke Junie from within Junie. Use a different target CLI."

Step 2: Execute Shared Procedure

  1. Read references/shared-procedure.md for the core workflow (mode inference, context gathering, prompt construction, result presentation).
  2. Read references/cli-junie.md for Junie-specific flags, model selection heuristics, and version compatibility matrix.
  3. Follow the shared procedure using the Junie-specific details.
Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 28 lines · 83 tokens per session scan A 29e4499a1e46

Subscribe to this mod's changes

junie is a skill published in the GitHub repository darshitpp/x-agent (2 stars, last pushed 23d ago), licensed MIT. It adds 83 tokens to every session and 244 once invoked, about $0.0004 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 2026-08-31.

Related

Other skills, from other repositories

architecture-refiner

Facilitate a structured conversation to define architecture principles for a repository. Supports multiple architecture styles: clean architecture (default), hexagonal / ports & adapters, modular monolith, or custom. Produces a formal architecture document that the corresponding atom will use. Use when setting up a…

techygarg/lattice · 114 tokens

lattice-init

Guided setup and upgrade-check experience for Lattice projects -- scans the repository, detects existing configuration and outdated conventions, suggests refiners and available upgrades in priority order, and creates or reconciles the .lattice/ config. Bridges the gap between installing skills and getting first value…

techygarg/lattice · 115 tokens

intelligent-investor-graham

Use Graham value investing for Is this investment or speculation, defensive stock screens, margin of safety, Mr. Market, allocation, funds, IPOs.

simbajigege/book2skills · 37 tokens

skill-to-workflow

将现有 Skill、Prompt、SOP 或 Agent 操作说明拆解为可执行、可监控、可重试的 Workflow 规格;识别真实节点、共享子工作流、工具调用、状态、分支、循环、 提示词、数据契约和验收方式。适用于用户要求把一个 Skill 转成工作流、节点图、 编排方案或 Workflow 实现规格时;不替代原 Skill 执行业务任务,也不在未要求时 绑定具体工作流平台或直接部署。.

simbajigege/book2skills · 120 tokens

query-loop-implementation

Implement a production-ready LLM query loop / agent loop for AI applications. Use this skill whenever the user wants to add tool calling, ReAct-style reasoning-action-observation cycles, function calling loops, query engines, agent runtimes, toolresult feedback, max-turn exits, or Claude Code-like Agent Loop behavior…

simbajigege/book2skills · 75 tokens

cncf-landscape

Use this skill when discovering and comparing cloud-native technologies from the CNCF Landscape for an architecture or engineering decision. Query the live public Landscape API, filter candidates by capability, category, maturity, license, and repository signals, then produce an evidence-backed shortlist with…

magnus919/agent-skills · 90 tokens