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 agentmods add skills/vudovn/ag-kit/skillifynpx skills add vudovn/ag-kit --skill skillifygit clone --depth 1 https://github.com/vudovn/ag-kitWhat 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 | $0.00037 | $0.00805 |
| Opus 5 | $0.00018 | $0.00402 |
| Sonnet 5 | $0.00007 | $0.00161 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
skillify 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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skillify — Auto-Create Skills from Workflows
Turn repetitive patterns into reusable skills. If you've done it three times, it should be a skill.
When to Skillify
✅ Good candidates:
- You've seen the user ask for the same type of work 3+ times
- A workflow involves 5+ consistent steps
- The pattern works across different projects
- Other agents could benefit from this knowledge
❌ Bad candidates:
- One-off tasks (just do them)
- Project-specific hacks (use memory instead)
- Already covered by existing skills (check first)
Skill Creation Protocol
Step 1: Identify the Pattern
What triggers this workflow? (user says X, file type Y, domain Z)
What steps are always the same?
What parts vary between uses?
What's the expected output?
Step 2: Generate SKILL.md
Use this template:
---
name: [kebab-case-name]
description: [One sentence describing what this skill does]
when_to_use: "[When the user asks X, works with Y files, or Z domain. NOT for A.]"
allowed-tools: [Read, Write, Edit, Grep, Glob, Bash — only what's needed]
effort: [low | medium | high]
---
# [Skill Name] — [Short Subtitle]
> [One-line philosophy or principle]
## Overview
[2-3 sentences explaining what this skill enables]
## When to Use
✅ Good for: [list]
❌ Not for: [list]
## Protocol
### Step 1: [First Action]
[Instructions]
### Step 2: [Second Action]
[Instructions]
### Step N: [Verification]
[How to verify the skill worked correctly]
## Best Practices
[3-5 key rules]
Step 3: Place the Skill
.agents/skills/[skill-name]/SKILL.md
Step 4: Verify
- Frontmatter has all required fields (name, description, when_to_use)
-
when_to_useclearly defines triggers AND exclusions - Steps are actionable, not vague
- Skill doesn't duplicate an existing one
Naming Conventions
| Pattern | Skill Name | Example |
|---|---|---|
| Action-based | [verb]-[noun] |
verify-changes, batch-operations |
| Domain-based | [domain]-[aspect] |
database-design, api-patterns |
| Tool-based | [tool]-patterns |
tailwind-patterns, prisma-expert |
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.
- 2d ago First seen · 117 lines · 37 tokens per session scan A e95a98f0baba
skillify is a skill published in the GitHub repository vudovn/ag-kit (8,162 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 805 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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