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 beel-collab/presets.dev --skill web-scrapergit clone --depth 1 https://github.com/beel-collab/presets.devWrote 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/beel-collab/presets.dev/web-scraper)<a href="https://agentmods.dev/skills/beel-collab/presets.dev/web-scraper"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/web-scraper.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 5.1 | $0.00039 | $0.06464 |
| Opus 5 | $0.00019 | $0.03232 |
| Sonnet 5 | $0.00008 | $0.01293 |
| Haiku 4.5 | $0.00004 | $0.00646 |
Grade C, and why
web-scraper scanned grade C with 2 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 3d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s "XML_URL" | python3 -c " Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Multi-strategy**: WebFetch (static), Browser automation (JS-rendered), Bash/curl (APIs), WebSearch (discovery) How it starts
The opening of the file, as written. The whole thing — 747 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Scraper
Overview
Web scraping inteligente multi-estrategia. Extrai dados estruturados de paginas web (tabelas, listas, precos). Paginacao, monitoramento e export CSV/JSON.
When to Use This Skill
- When the user mentions "scraper" or related topics
- When the user mentions "scraping" or related topics
- When the user mentions "extrair dados web" or related topics
- When the user mentions "web scraping" or related topics
- When the user mentions "raspar dados" or related topics
- When the user mentions "coletar dados site" or related topics
Do Not Use This Skill When
- The task is unrelated to web scraper
- A simpler, more specific tool can handle the request
- The user needs general-purpose assistance without domain expertise
How It Works
Execute phases in strict order. Each phase feeds the next.
1. CLARIFY -> 2. RECON -> 3. STRATEGY -> 4. EXTRACT -> 5. TRANSFORM -> 6. VALIDATE -> 7. FORMAT
Never skip Phase 1 or Phase 2. They prevent wasted effort and failed extractions.
Fast path: If user provides URL + clear data target + the request is simple (single page, one data type), compress Phases 1-3 into a single action: fetch, classify, and extract in one WebFetch call. Still validate and format.
Capabilities
- Multi-strategy: WebFetch (static), Browser automation (JS-rendered), Bash/curl (APIs), WebSearch (discovery)
- Extraction modes: table, list, article, product, contact, FAQ, pricing, events, jobs, custom
- Output formats: Markdown tables (default), JSON, CSV
- Pagination: auto-detect and follow (page numbers, infinite scroll, load-more)
- Multi-URL: extract same structure across sources with comparison and diff
- Validation: confidence ratings (HIGH/MEDIUM/LOW) on every extraction
- Auto-escalation: WebFetch fails silently -> automatic Browser fallback
- Data transforms: cleaning, normalization, deduplication, enrichment
- Differential mode: detect changes between scraping runs
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.
- 3d ago First seen · 747 lines · 39 tokens per session scan C 963fc583cf76
web-scraper is a skill published in the GitHub repository beel-collab/presets.dev (2 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 6,464 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
skill-creator-primer
You MUST load this skill before the skill-creator skill AND before making ANY change to, or conducting a review of ANY Agent Skill. Triggers include creating, editing, reviewing, or contributing to any part of an Agent Skill (description, frontmatter, body, references, scripts, trigger evals, conflicts, etc).
llm-wiki
Use when building or maintaining a self-contained personal knowledge base (an LLM wiki) in plain markdown. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki health, auditing article claims against their sources, critiquing a wiki source's reasoning, superseding stale knowledge, 'add to…
extract-wisdom
Extract wisdom, insights, and actionable takeaways from YouTube videos, blog posts, articles, or text files. Use when asked to extract wisdom or key insights from a given content source.
apply-mantel-styles
Provides guidelines for applying Mantel's brand styles to diagrams and frontend components. Use when asked to create visuals that need to align with Mantel's branding.
home-assistant
This skill should be used when helping with Home Assistant setup, including creating automations, modifying dashboards, checking entity states, debugging automations, and managing the smart home configuration. Use this for queries about HA entities, YAML automation/dashboard generation, or troubleshooting HA issues.
deepeval
Use when discussing or working with DeepEval (the python AI evaluation framework).