Agent Development

Guidance for creating agents for Claude Code plugins. An agent is an autonomous helper that handles a complex, multi-step task independently.

In plain words
What is it for?
Use it to write agent files, YAML frontmatter, system prompts, triggering examples, tool lists, model settings, and color settings.
Why use it?
It helps define when an agent should start, what it should do, which model and tools it can use, and how its configuration file should be structured.

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/xyruscode/ai-sync/agent-development
Any agent
npx skills add XyrusCode/ai-sync --skill agent-development
Clone the repo
git clone --depth 1 https://github.com/XyrusCode/ai-sync

Made for: Claude Code, Codex.

Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,484 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod 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 $0.00080 $0.02484
Opus 5 $0.00040 $0.01242
Sonnet 5 $0.00016 $0.00497
Haiku 4.5 $0.00008 $0.00248

Measured yesterday against content hash ff3324078bbe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Agent Development 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate-agent.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

91% identical to agent-identifier — 23 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/agent-development/SKILL.md · 416 lines

How it starts

The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Development for Claude Code Plugins

Overview

Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities.

Key concepts:

  • Agents are FOR autonomous work, commands are FOR user-initiated actions
  • Markdown file format with YAML frontmatter
  • Triggering via description field with examples
  • System prompt defines agent behavior
  • Model and color customization

Agent File Structure

Complete Format

---
name: agent-identifier
description: Use this agent when [triggering conditions]. Examples:

<example>
Context: [Situation description]
user: "[User request]"
assistant: "[How assistant should respond and use this agent]"
<commentary>
[Why this agent should be triggered]
</commentary>
</example>

<example>
[Additional example...]
</example>

model: inherit
color: blue
tools: ["Read", "Write", "Grep"]
---

You are [agent role description]...

**Your Core Responsibilities:**
1. [Responsibility 1]
2. [Responsibility 2]

**Analysis Process:**
[Step-by-step workflow]

**Output Format:**
[What to return]

Frontmatter Fields

name (required)

Agent identifier used for namespacing and invocation.

Format: lowercase, numbers, hyphens only Length: 3-50 characters Pattern: Must start and end with alphanumeric

Good examples:

  • code-reviewer
  • test-generator
  • api-docs-writer
  • security-analyzer

Bad examples:

  • helper (too generic)
  • -agent- (starts/ends with hyphen)
  • my_agent (underscores not allowed)
  • ag (too short, < 3 chars)

description (required)

Defines when Claude should trigger this agent. This is the most critical field.

Must include:

  1. Triggering conditions ("Use this agent when...")
  2. Multiple <example> blocks showing usage
  3. Context, user request, and assistant response in each example
  4. <commentary> explaining why agent triggers

Read the full file on GitHub · 416 lines

Files

What ships with it

6 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. yesterday First seen · 416 lines · 80 tokens per session scan A ff3324078bbe

Subscribe to this mod's changes

Agent Development is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 2,484 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to agent-identifier, differing in 23 lines, and is treated as a copy.

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