agent-design

A guide for creating specialist agent definitions for CodingBuddy. It covers the agent's expertise, system instructions, activation conditions, and limits so each agent has a distinct role.

In plain words
What is it for?
Use it to add or improve an agent, define its JSON schema, write its system prompt, set activation triggers, and check how it differs from existing agents.
Why use it?
It helps prevent overlapping agents and makes it clearer when a specialist should or should not be used.

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/jeremydev87/codingbuddy/agent-design
Any agent
npx skills add JeremyDev87/codingbuddy --skill agent-design
Clone the repo
git clone --depth 1 https://github.com/JeremyDev87/codingbuddy

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,996 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 $0.00033 $0.01996
Opus 5 $0.00016 $0.00998
Sonnet 5 $0.00007 $0.00399
Haiku 4.5 $0.00003 $0.00200

Measured 2d ago against content hash 2b1ac33d8420, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-design 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.

packages/rules/.ai-rules/skills/agent-design/SKILL.md · 275 lines

How it starts

The opening of the file, as written. The whole thing — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Design

Overview

Agents are specialist personas that AI assistants embody to provide focused, domain-specific guidance. A well-designed agent has a clear identity, distinct expertise, and precise activation triggers.

Core principle: Each agent does ONE thing exceptionally well. Overlap is a design flaw.

Iron Law:

DEFINE THE AGENT'S "NO" BEFORE DEFINING ITS "YES"
What this agent explicitly does NOT handle is as important as what it does.

When to Use

  • Adding a new specialist domain to codingbuddy
  • Improving an existing agent's focus and expertise
  • Designing agent activation trigger patterns
  • Reviewing agent differentiation before adding to the registry

Agent Schema Reference

Agents are defined in packages/rules/.ai-rules/agents/<name>.json (filename is kebab-case):

{
  "name": "My Specialist",
  "description": "One-sentence description of what this agent specializes in",
  "role": {
    "title": "Specialist Role Title",
    "type": "specialist",
    "expertise": [
      "Domain Expertise Area 1",
      "Domain Expertise Area 2",
      "Domain Expertise Area 3"
    ],
    "responsibilities": [
      "Key responsibility 1",
      "Key responsibility 2"
    ]
  },
  "context_files": [
    ".ai-rules/rules/core.md",
    ".ai-rules/rules/project.md"
  ],
  "modes": {
    "planning": {
      "activation": { "trigger": "When planning..." }
    },
    "evaluation": {
      "activation": { "trigger": "When evaluating..." }
    }
  }
}

Required Fields

Field Type Rules
name string Display name, Title Case (e.g., "Migration Specialist")
description string 10+ chars, one sentence
role object Must include title at minimum
role.title string Official role title
role.expertise string[] 3-7 items, specific domains
context_files string[] Paths starting with .ai-rules/

Note: The JSON filename uses kebab-case (e.g., migration-specialist.json), while name is Title Case.

Read the full file on GitHub · 275 lines

Files

What ships with it

2 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 · 275 lines · 33 tokens per session scan A 2b1ac33d8420

Subscribe to this mod's changes

agent-design is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 1,996 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.

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