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 The-AI-Directory-Company/agents-and-skills --skill create-agent-markdowngit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-skillsWrote 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/the-ai-directory-company/agents-and-skills/create-agent-markdown)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/create-agent-markdown"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/create-agent-markdown/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/the-ai-directory-company/agents-and-skills/create-agent-markdown"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/create-agent-markdown.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 | $0.00039 | $0.02122 |
| Opus 5 | $0.00019 | $0.01061 |
| Sonnet 5 | $0.00008 | $0.00424 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
create-agent-markdown 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 9d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Agent Markdown
You are creating an agent definition file for the AI-Directory — a curated directory of the highest-quality AI agent definitions in the Agent Skills ecosystem. Every agent you create must meet a quality bar that makes it genuinely useful as a behavioral prompt, not just a role description.
Before you start
Gather the following. If anything is missing, ask before proceeding:
- Role name — What is this agent? (e.g., "Software Architect", "Security Auditor")
- Core domain — What field does this agent operate in?
- Target user — Who would use this agent? What problem does it solve for them?
- Existing references — Are there existing agent definitions, system prompts, or job descriptions to draw from?
- Complementary agents/skills — What other agents or skills in the directory would pair well with this one?
The golden standard
An agent definition is a behavioral prompt — it changes how the AI thinks, not just what it does. The body must contain real domain expertise that an AI cannot derive from generic training data.
What separates great from mediocre
| Great agent definition | Mediocre agent definition |
|---|---|
| Specific mental models the agent uses to think | Vague descriptions of what the role does |
| Decision heuristics with real tradeoffs | Generic advice like "be thorough" |
| Concrete examples of reasoning patterns | Abstract principles without application |
| Clear boundaries — what this agent refuses to do | No constraints, tries to do everything |
| Domain-specific vocabulary and frameworks | Generic corporate language |
| Prioritized layers of concern | Flat lists of responsibilities |
The "colleague test"
Before finalizing, ask: "If a real professional in this role read this, would they nod and say 'yes, this is how I actually think'?" If the answer is no, the definition needs more domain-specific substance.
File structure
Frontmatter (YAML)
---
name: <slug>
description: <what this agent does and when to use it — max 1024 chars>
metadata:
displayName: "<Human-Readable Name>"
categories: ["<primary-category>"]
tags: ["<tag1>", "<tag2>", "<tag3>"]
worksWellWithAgents: ["<agent-slug>"]
worksWellWithSkills: ["<skill-slug>"]
---
What ships with it
4 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.
- 9d ago First seen · 200 lines · 39 tokens per session scan A 8d561813a226
create-agent-markdown is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 2,122 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 2026-09-03.
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