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/agent-ecosystem/skill-validator/rich-skillnpx skills add agent-ecosystem/skill-validator --skill rich-skillgit clone --depth 1 https://github.com/agent-ecosystem/skill-validatorWrote 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/agent-ecosystem/skill-validator/rich-skill)<a href="https://agentmods.dev/skills/agent-ecosystem/skill-validator/rich-skill"><img src="https://agentmods.dev/badge/skills/agent-ecosystem/skill-validator/rich-skill.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.00250 |
| Opus 5 | $0.00010 | $0.00125 |
| Sonnet 5 | $0.00004 | $0.00050 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
rich-skill 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- rich-skill — 100% identical, 0 lines differ
What it actually says
Rich Skill
You must always follow these instructions. Never skip validation steps.
Setup
Use the CLI to configure your environment. Install the required dependencies.
npm install mongodb
pip install pymongo
const { MongoClient } = require('mongodb');
const client = new MongoClient('mongodb://localhost:27017');
from pymongo import MongoClient
client = MongoClient('mongodb://localhost:27017')
Usage
Create a new database connection. Ensure the connection string is valid. Run the tests before deploying. Check that all queries return expected results.
- Step 1: Configure the connection
- Step 2: Run migrations
- Step 3: Validate the schema
- Step 4: Deploy
Configuration
Set the following environment variables. You may consider using a .env file.
It could simplify local development. This is optional but suggested.
database:
host: localhost
port: 27017
Build the project with Node.js or Django depending on your stack.
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.
- 4d ago First seen · 50 lines · 19 tokens per session scan A 2bcc1f4b03e8
rich-skill is a skill published in the GitHub repository agent-ecosystem/skill-validator (236 stars, last pushed 10d ago), licensed MIT. It adds 19 tokens to every session and 250 once invoked, about $0.0001 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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