Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Casper-Studios/casper-marketplacenpx agentmods add skills/casper-studios/casper-marketplace/apify-scrapersWrote 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/casper-studios/casper-marketplace/apify-scrapers)<a href="https://agentmods.dev/skills/casper-studios/casper-marketplace/apify-scrapers"><img src="https://agentmods.dev/badge/skills/casper-studios/casper-marketplace/apify-scrapers/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/casper-studios/casper-marketplace/apify-scrapers"><img src="https://agentmods.dev/badge/skills/casper-studios/casper-marketplace/apify-scrapers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 72 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00105 | $0.03559 |
| Opus 5 | $0.00053 | $0.01780 |
| Sonnet 5 | $0.00021 | $0.00712 |
| Haiku 4.5 | $0.00011 | $0.00356 |
Grade A, and why
apify-scrapers 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 12d 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 — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apify Scrapers
Overview
Scrape content from major social platforms using Apify actors. Each platform has optimized settings for cost and quality.
Quick Decision Tree
What do you want to scrape?
│
├── Social Media Posts
│ ├── Twitter/X → references/twitter.md
│ │ └── Script: scripts/scrape_twitter_ai_trends.py
│ │
│ ├── Reddit → references/reddit.md
│ │ └── Script: scripts/scrape_reddit_ai_tech.py
│ │
│ ├── LinkedIn → references/linkedin.md
│ │ └── Script: scripts/scrape_linkedin_posts.py
│ │
│ ├── Instagram → references/instagram.md
│ │ └── Script: scripts/scrape_instagram.py
│ │ └── Modes: profile, posts, hashtag, reels, comments
│ │
│ ├── Facebook → references/facebook.md
│ │ └── Script: scripts/scrape_facebook.py
│ │ └── Modes: page, posts, reviews, groups, marketplace
│ │
│ ├── TikTok → references/multi-platform.md
│ │ └── Script: scripts/scrape_multi_platform.py
│ │
│ └── YouTube → references/multi-platform.md
│ └── Script: scripts/scrape_multi_platform.py
│
├── Business/Places
│ ├── Google Maps businesses → references/google-maps.md
│ │ └── Script: scripts/scrape_google_maps.py
│ │ └── Modes: search, place, reviews
│ │
│ └── Contact info from websites → references/contact-enrichment.md
│ └── Script: scripts/scrape_contact_info.py
│ └── Extract: emails, phone numbers, social profiles
│
├── Auto-detect URL type → references/url-detect.md
│ └── Script: scripts/scrape_content_by_url.py
│
├── Trend Analysis (NEW)
│ └── Enriched trend analysis → workflows/trend-analysis.md
│ └── Script: scripts/analyze_trends.py
│ └── Features: velocity scoring, lifecycle staging, opportunity scoring
│
└── Workflows (multi-step)
├── Lead generation → workflows/lead-generation.md
├── Influencer discovery → workflows/influencer-discovery.md
├── Competitor analysis → workflows/competitor-intel.md
├── Trend analysis → workflows/trend-analysis.md
└── Competitor Ads Intelligence (NEW) → workflows/competitor-ads.md
└── Script: scripts/scrape_competitor_ads.py
└── Platforms: Facebook Ads Library, Google Ads Transparency
└── Features: Spend estimates, creative analysis, benchmarking
What ships with it
28 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.
- references/contact-enrichment.md 2.2 KB
- references/facebook.md 12 KB
- references/google-maps.md 8.7 KB
- references/instagram.md 15 KB
- references/linkedin.md 4.5 KB
- references/multi-platform.md 4.5 KB
- references/reddit.md 4.0 KB
- references/twitter.md 3.7 KB
- references/url-detect.md 4.8 KB
- references/workflows/audience-analysis.md 11 KB
- references/workflows/competitor-ads.md 19 KB
- references/workflows/competitor-intel.md 2.8 KB
- references/workflows/influencer-discovery.md 18 KB
- references/workflows/lead-generation.md 1.7 KB
- references/workflows/trend-analysis.md 16 KB
- scripts/analyze_audience.py 62 KB runs code
- scripts/analyze_trends.py 72 KB runs code
- scripts/discover_influencers.py 46 KB runs code
- scripts/enrich_contacts.py 11 KB runs code
- scripts/scrape_competitor_ads.py 32 KB runs code
- scripts/scrape_content_by_url.py 17 KB runs code
- scripts/scrape_facebook.py 20 KB runs code
- scripts/scrape_google_maps.py 19 KB runs code
- scripts/scrape_instagram.py 27 KB runs code
- scripts/scrape_linkedin_posts.py 10 KB runs code
- scripts/scrape_multi_platform.py 7.9 KB runs code
- scripts/scrape_reddit_ai_tech.py 9.7 KB runs code
- scripts/scrape_twitter_ai_trends.py 8.0 KB runs code
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.
- 12d ago First seen · 363 lines · 105 tokens per session scan A afa9d9f77567
apify-scrapers is a skill published in the GitHub repository Casper-Studios/casper-marketplace (12 stars, last pushed 7d ago), licensed MPL-2.0. It adds 105 tokens to every session and 3,559 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
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