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 anton-abyzov/vskill --skill apify-data-gatheringgit clone --depth 1 https://github.com/anton-abyzov/vskillWrote 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/anton-abyzov/vskill/apify-data-gathering)<a href="https://agentmods.dev/skills/anton-abyzov/vskill/apify-data-gathering"><img src="https://agentmods.dev/badge/skills/anton-abyzov/vskill/apify-data-gathering/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/anton-abyzov/vskill/apify-data-gathering"><img src="https://agentmods.dev/badge/skills/anton-abyzov/vskill/apify-data-gathering.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 | $0.00143 | $0.01815 |
| Opus 5.5 | $0.00057 | $0.00726 |
| Sonnet 5.5 | $0.00029 | $0.00363 |
| Haiku 4.5 | $0.00014 | $0.00181 |
Grade A, and why
apify-data-gathering scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| 1 | Plain fetch and parse (curl/httpx + selectors, or a single-page fetch tool) | $0 | Static HTML, a handful of pages, no bot wall. | How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apify data gathering
Apify is a fetch layer: maintained scrapers (Actors), browsers, proxies and storage you pay for per result or per compute unit. It is not a strategy. This skill decides when Apify is the right door, keeps every run inside a budget, and leaves a dataset someone can audit.
The official apify/agent-skills teach the platform (Actor catalogue, building Actors). This skill is the operating discipline around them: door choice, legality, budget, caching, evidence. Use both if both are installed.
1. Pick the door, cheapest first
| Tier | Door | Cost | Use when |
|---|---|---|---|
| 0 | Official API, export, RSS, sitemap, JSON-LD, the site's own XHR/GraphQL | $0 | Always check first. GitHub API, HN Algolia API, YouTube Data API, Reddit JSON, Google Places API, a league's JSON endpoint. |
| 1 | Plain fetch and parse (curl/httpx + selectors, or a single-page fetch tool) | $0 | Static HTML, a handful of pages, no bot wall. |
| 2 | Apify Store Actor | per result / per event | A maintained Actor exists for the site (Maps, Instagram, X, TikTok, Google SERP, reviews), or you need JS rendering or proxies at volume. |
| 3 | Generic crawler Actor (apify/website-content-crawler, apify/cheerio-scraper) or a custom Actor |
compute units | Long-tail sites at volume, docs ingestion for RAG. |
Rules that override the table:
- For anything that runs on a schedule, compile a deterministic extractor once (selectors or a typed provider) and replay it. Do not call an LLM on every fetch; it creates drift and duplicates. Re-run the LLM only when health checks fail.
- Hash the fetched content and skip unchanged pages before paying for extraction.
- If the only way in is defeating a login, CAPTCHA, WAF challenge or honeypot aimed at you, stop and ask the user. Tooling being legal says nothing about the target allowing it.
2. Legal and data gate (before any run)
- Read the target's terms and robots.txt. If the terms forbid automated access, say so and ask for an alternative (official API, partner export, written permission).
- Public data only. Never use your own logged-in cookies with an Actor (LinkedIn, Facebook, Instagram private views). Logged-in scraping breaks those platforms' terms and risks the account.
- Personal data: collect only business-contact fields the task needs, record the source URL for each row, and honour suppression lists. Cold email needs CAN-SPAM (US) or GDPR/PECR (UK/EU) compliance: opt-out, physical address, lawful basis.
- Respect rate limits and honeypots: fetch only known URL shapes, no blind link following on sites that trap crawlers.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 81 lines · 143 tokens per session scan A c6f35f375785
apify-data-gathering is a skill published in the GitHub repository anton-abyzov/vskill (48 stars, last pushed yesterday), licensed MIT. It adds 143 tokens to every session and 1,815 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-18.
Other skills, from other repositories
start-coding-task
Start a CodeAgent coding task from the user's request on one of their existing sessions, and report the session id so they can follow it.
review-agent-work
Review the changes a CodeAgent session made, and open or review a pull request when the user asks.
continue-with-codeagent-credits
Switch a session to a CodeAgent managed agent billed from the user's prepaid credits, with the user's explicit confirmation.
supervise-session
Monitor, redirect, answer or stop an existing CodeAgent session.
prereview
Review the current diff against this team's conventions and invariants before it ships. Invoke with /prereview before opening a PR, or run as a pre-push gate.
agent-config-setup
Generate AI agent config files for any project — Cursor, Claude Code, Copilot, Windsurf, Cline, AGENTS.md. Use when setting up a new project for AI agents.