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 dhaupin/vant --skill vant-skill-environmentgit clone --depth 1 https://github.com/dhaupin/vantWrote 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/dhaupin/vant/vant-skill-environment)<a href="https://agentmods.dev/skills/dhaupin/vant/vant-skill-environment"><img src="https://agentmods.dev/badge/skills/dhaupin/vant/vant-skill-environment/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/dhaupin/vant/vant-skill-environment"><img src="https://agentmods.dev/badge/skills/dhaupin/vant/vant-skill-environment.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 | $0.00005 | $0.00223 |
| Opus 5.5 | $0.00002 | $0.00089 |
| Sonnet 5.5 | $0.00001 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
environment 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.
What it actually says
Environment
Environment variables.
When To Use
- Config secrets
- API keys
- Environment-specific settings
What To Do
1. Files
| File | What |
|---|---|
| .env | Local (gitignore) |
| .env.local | Local override |
| .env.production | Production |
2. Syntax
API_KEY=secret123
DATABASE_URL=postgres://localhost
DEBUG=true
3. Load
// Node
require('dotenv').config()
process.env.API_KEY
# Python
from dotenv import load_dotenv
load_dotenv()
os.environ['API_KEY']
4. Best Practice
- Never commit secrets
- Use different values per env
- Validate required vars
Role: Environment Manager
Input: .env files
Output: Config
Secrets.
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 · 67 lines · 5 tokens per session scan A 3708427c4134
environment is a skill published in the GitHub repository dhaupin/vant (12 stars, last pushed yesterday), licensed MIT. It adds 5 tokens to every session and 223 once invoked, about $0.0000 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 2026-08-31.
Other skills, from other repositories
groq-inference
Ultra-fast LLM inference on custom LPU hardware. OpenAI-compatible API at api.groq.com. Lowest latency in the industry (500-1000+ tok/s). Supports chat completions, vision, audio (Whisper STT + TTS), tool calling, JSON mode, and streaming. Free tier available. Inference only — no training.
wikipedia
Search and read Wikipedia via x wkp — MediaWiki API, no API key, zero install; query, extract, suggest, and DDG route in one module. Load for wiki, wikipedia, encyclopedia lookup, article summary.
pr-writing-review
Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer…
session-investigator
Investigate fast-agent session and history files to diagnose issues. Use when a session ended unexpectedly, when debugging tool loops, when correlating sub-agent traces with main sessions, or when analyzing conversation flow and timing. Covers session.json metadata, history JSON format, message structure, tool…
cve
Look up CVE records via x cve — cached, zero-API-key, daily xz TSV. Load for cve, vulnerability id, kev, epss, nvd, cvelist, or security advisory.
bun-file-io
Use this when you are working on file operations like reading, writing, scanning, or deleting files. It summarizes the preferred file APIs and patterns used in this repo. It also notes when to use filesystem helpers for directories.