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 ArcedeDev/air-sdk --skill clawhub-skillgit clone --depth 1 https://github.com/ArcedeDev/air-sdkWrote 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/arcededev/air-sdk/clawhub-skill)<a href="https://agentmods.dev/skills/arcededev/air-sdk/clawhub-skill"><img src="https://agentmods.dev/badge/skills/arcededev/air-sdk/clawhub-skill/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/arcededev/air-sdk/clawhub-skill"><img src="https://agentmods.dev/badge/skills/arcededev/air-sdk/clawhub-skill.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 | $0.00041 | $0.00861 |
| Opus 5.5 | $0.00016 | $0.00344 |
| Sonnet 5.5 | $0.00008 | $0.00172 |
| Haiku 4.5 | $0.00004 | $0.00086 |
Grade A, and why
air-sdk 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AIR SDK — Collective Web Intelligence
You have 4 MCP tools from AIR SDK. They give you shared knowledge about websites — what actions are possible, which CSS selectors work, and what other agents have already figured out.
When to use these tools
- User asks you to do something on a website (search, buy, extract data, compare prices)
- User asks what's possible on a site
- User asks you to extract or scrape data from a URL
- You need to interact with a website and want to know the correct selectors before navigating
Workflow: browse, execute, act, report
Always follow this order:
Step 1: Browse capabilities
Before navigating to any site, check what's known about it:
Tool: browse_capabilities
Input: { "domain": "amazon.com" }
This returns capabilities (search, purchase, filter, etc.) with confidence scores and available macros.
Step 2: Execute a capability
Get the specific execution plan with CSS selectors:
Tool: execute_capability
Input: { "domain": "amazon.com", "capability": "search_products", "parameters": { "query": "wireless headphones" } }
This returns step-by-step instructions: which URL to visit, which selectors to click/fill, in what order.
Step 3: Act in the browser
Use the CSS selectors from Step 2 to perform the actions. The selectors have been verified by other agents.
Step 4: Report what happened
Always report the outcome. This is how the network learns:
Tool: report_outcome
Input: {
"domain": "amazon.com",
"capability": "search_products",
"success": true,
"steps": [
{ "action": "click", "selector": "input#twotabsearchtextbox", "success": true },
{ "action": "fill", "selector": "input#twotabsearchtextbox", "value": "wireless headphones", "success": true },
{ "action": "click", "selector": "input#nav-search-submit-button", "success": true }
]
}
You MUST include the actual CSS selectors you used. Reports without selectors are discarded.
Extracting data
To extract structured data from any URL without browser automation:
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 · 118 lines · 41 tokens per session scan A 99683216bfbc
air-sdk is a skill published in the GitHub repository ArcedeDev/air-sdk (1 stars, last pushed 6mo ago), licensed MIT. It adds 41 tokens to every session and 861 once invoked, about $0.0002 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.
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