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.
npx skills add JeremyDev87/codingbuddy --skill agent-designgit clone --depth 1 https://github.com/JeremyDev87/codingbuddyWrote 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.
[](https://agentmods.dev/skills/jeremydev87/codingbuddy/agent-design)<a href="https://agentmods.dev/skills/jeremydev87/codingbuddy/agent-design"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/agent-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jeremydev87/codingbuddy/agent-design"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/agent-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.01996 |
| Opus 5.5 | $0.00013 | $0.00798 |
| Sonnet 5.5 | $0.00007 | $0.00399 |
| Haiku 4.5 | $0.00003 | $0.00200 |
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 1mo 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.
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), whilenameis Title Case.
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.
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.
- 1mo ago First seen · 275 lines · 33 tokens per session scan A 2b1ac33d8420
agent-design is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 6mo ago), licensed MIT. It adds 33 tokens to every session and 1,996 once invoked, about $0.0001 per session on Opus 5.5. 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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