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 NovadaLabs/Novada-mcp --skill novada-extractgit clone --depth 1 https://github.com/NovadaLabs/Novada-mcpWrote 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/novadalabs/novada-mcp/novada-extract)<a href="https://agentmods.dev/skills/novadalabs/novada-mcp/novada-extract"><img src="https://agentmods.dev/badge/skills/novadalabs/novada-mcp/novada-extract/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/novadalabs/novada-mcp/novada-extract"><img src="https://agentmods.dev/badge/skills/novadalabs/novada-mcp/novada-extract.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 | $0.00000 | $0.00590 |
| Opus 5.5 | $0.00000 | $0.00236 |
| Sonnet 5.5 | $0.00000 | $0.00118 |
| Haiku 4.5 | $0.00000 | $0.00059 |
Grade A, and why
novada-extract 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 2mo 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
novada_extract — Extraction Specialist Skill
When to use: You have a URL and need its content. This is the primary content extraction tool.
Decision: Which render mode?
| Site type | Recommended | Reason |
|---|---|---|
| News, docs, blogs | render=auto (default) | Static fetch works, 112ms avg |
| LinkedIn, Glassdoor, React SPA | render=render | JS-rendered, needs Web Unblocker |
| Behind login, interactive | render=browser | Full Chromium CDP |
Rule: Never use render=render for ALL pages. auto is 15-113x faster.
Batch extraction pattern
{
"url": ["https://site.com/page1", "https://site.com/page2", "https://site.com/page3"],
"render": "auto",
"max_chars": 25000
}
Returns one labeled section per URL: ### [1/3] url.
Field extraction pattern
{
"url": "https://amazon.com/product/...",
"fields": ["price", "rating", "availability", "brand"]
}
Checks JSON-LD first, then pattern matching. Returns ## Requested Fields block.
Content too long?
Use max_chars=50000 for long docs. Default is 25000. Max is 100000.
{
"url": "https://long-doc.com/guide",
"max_chars": 50000
}
Bot-blocked / empty content?
Escalate: static → render → browser.
{"url": "...", "render": "render"}
If still blocked:
{"url": "...", "render": "browser"}
Common Mistakes
- ❌ Setting render=render on all calls — adds 9-16s latency on pages that don't need it
- ❌ Calling novada_extract to check if a URL exists — use novada_map for URL discovery
- ❌ Setting max_chars=100000 by default — use 25000, increase only when needed
After extraction
- Content looks JS-heavy or incomplete → retry with render=render
- Content is truncated → increase max_chars
- Need more URLs → call novada_map first, then batch extract
When to call extract after search
novada_search returns snippets only — they locate pages but do not answer questions. If accuracy matters (facts, prices, current events), call novada_extract on the top 1-3 search results and read the full content before answering. For multi-source questions, novada_research (which calls extract internally on top sources) is cheaper than doing this manually — prefer it when you need ≥2 sources.
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.
- 2mo ago First seen · 77 lines · 0 tokens per session scan A 1907bfe06055
novada-extract is a skill published in the GitHub repository NovadaLabs/Novada-mcp (3 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 590 tokens. 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.
novada-extract compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| novada-extractNovadaLabs/Novada-mcp | Skill | 3 | today | MIT | A | 0 | Claude Code, Codex |
| web-readingellmos-ai/skills | Skill | 9 | 4d ago | MIT | A | 56 | Claude Code, Codex |
| crawl4ai-skilllancelin111/crawl4ai-skill | Skill | 17 | 8mo ago | MIT | A | 63 | Claude Code, Codex |
| x402browser-use/browser-use | Skill | 120k | yesterday | MIT | A | 175 | Claude Code |
| browser-usebrowser-use/browser-use | Skill | 120k | yesterday | MIT | A | 57 | Claude Code, Codex |
| blocked-page-recoveryNousResearch/hermes-agent | Skill | 261k | yesterday | MIT | A | 25 | Claude Code, Codex |
| playwrightopenai/openai-agents-python | Skill | 31k | yesterday | MIT | A | 19 | Claude Code, Codex |