apify-ultimate-scraper
Skill7 starsChanged 25 days agoApache-2.0View on GitHub
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.
- Installs packages
9 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- apify/apify-deepseek-harness-pluginedited, first seen Nov 8, 2026
- vines90/foreign-trade-cursor-skillstheir own version, first seen Nov 8, 2026
- EvezArt/evez-skillsedited, first seen Nov 1, 2026
- opradopedro/claude-skillsedited, first seen Oct 15, 2026
- hmzainjamil/claude-ai-skillsedited, first seen May 10, 2026
- hmzainjamil/claude-ai-systemtheir own version, first seen May 10, 2026
Other versions9 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- apify/agent-skills★ 2.5k66% same
- apify/apify-deepseek-harness-plugin★ 499% same
- EvezArt/evez-skills★ 377% same
- hmzainjamil/claude-ai-skills★ 312% same
- opradopedro/claude-skills★ 066% same
Wrote their own version · 4
- liangdabiao/fetch-everything★ 47same name
- vines90/foreign-trade-cursor-skills★ 9same name
- hmzainjamil/claude-ai-system★ 2same name
- samehjarour/apify-openclaw-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
The file
Show its rules and text
We split this skill into the rules it gives an agent
13 rules. 0 are common, 8 are distinctive, and 5 are very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
8
Distinctive
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 20
Exception: if --input returns no data, re-run with 2>&1 to confirm whether the cause is a missing schema vs.
- Distinctive: line 41
Before using the Apify CLI, always verify the local environment:
- Distinctive: line 43
Check that the CLI is installed and is v1.10.0 or newer:
- Distinctive: line 48
If this fails, install the CLI first:
- Distinctive: line 52
Check that the CLI is authenticated:
- Distinctive: line 58
If this shows the user is not logged in, instruct them to authenticate with a token:
- Very specific: line 80
Check .status for SUCCEEDED or FAILED.
- Very specific: line 85
Prefer apify-tier actors; use community-tier only when no apify actor covers the task.
- Very specific: line 87
If the output is empty, re-run without the redirect (2>&1) to surface auth or network errors before proceeding.
- Distinctive: line 89
If the task involves a multi-step pipeline, also read the matching workflow guide:
- Distinctive: line 108
If no Actor matches in the index, search dynamically:
- Very specific: line 122
If output is Error: No input schema found for this Actor, skip to source 2.
- Distinctive: line 149
Before starting the run, double-check whether the task is short enough for a blocking call or should use the async pattern from Step 0.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Universal web scraper
AI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI.
Rule: Pass --json and redirect stderr with 2>/dev/null on data-returning commands (actors call, actors start, actors info, actors search, datasets get-items, runs info). JSON output is stable across CLI versions. stderr contains progress messages and version warnings that break JSON parsers if not redirected.
This rule does not apply to status/auth commands (apify info, apify --version, apify login). For those, use 2>&1 so authentication and version errors are visible.
Exception: if --input returns no data, re-run with 2>&1 to confirm whether the cause is a missing schema vs. a network/auth error.
Rule: pass --user-agent apify-claude-code-plugin/apify-ultimate-scraper only on actor start and actor run commands (apify actors start, apify actors call). Do not add it to login, info, search, or other CLI commands.
Prerequisites
- Apify CLI v1.10.0+ (
npm install -g apify-cli). This matches the auth rules below. - Authenticated session (see below)
Authentication
On CLI v1.10.0 and earlier, only apify login --token TOKEN authenticates. Exporting APIFY_TOKEN does not.
From CLI v1.10.1, APIFY_TOKEN takes precedence over the stored login. export APIFY_TOKEN=... applies on v1.10.1 and later only.
Generate a token at https://console.apify.com/settings/integrations. Do not print it.
Workflow
Step 0: Verify CLI readiness before doing anything else
Before using the Apify CLI, always verify the local environment:
- Check that the CLI is installed and is v1.10.0 or newer:
apify --help
apify --versionIf this fails, install the CLI first:
npm install -g apify-cli- Check that the CLI is authenticated:
# Auth check — do NOT pipe to /dev/null, you need to see errors
apify info 2>&1If this shows the user is not logged in, instruct them to authenticate with a token:
apify login --token TOKEN- Authenticated Apify CLI commands need file access to
~/.apify/, where the CLI keeps its credentials. A host that sandboxes file access can deny this even when the login is valid; that is a sandbox problem, not a login problem. - Assume many Apify commands block with zero output until completion, so allow at least 60 seconds before treating one as stuck. If your shell tool takes a timeout, raise it accordingly.
- For long or unknown-duration runs, prefer the async pattern:
apify actors start "ACTOR_ID" -i 'JSON_INPUT' --user-agent apify-claude-code-plugin/apify-ultimate-scraper --json 2>/dev/nullThen poll the run status:
apify runs info RUN_ID --jsonCheck .status for SUCCEEDED or FAILED.
Step 1: Understand goal and select Actor
Identify the target platform and use case. Read references/actor-index.md to find the right Actor.
Prefer apify-tier actors; use community-tier only when no apify actor covers the task.
For input schemas, fetch dynamically: apify actors info "ACTOR_ID" --input --json 2>/dev/null
If the output is empty, re-run without the redirect (2>&1) to surface auth or network errors before proceeding.
If the task involves a multi-step pipeline, also read the matching workflow guide:
| Task involves... | Read |
| leads, contacts, emails, B2B | references/workflows/lead-generation.md |
| competitor, ads, pricing | references/workflows/competitive-intel.md |
| influencer, creator | references/workflows/influencer-vetting.md |
| brand, mentions, sentiment | references/workflows/brand-monitoring.md |
| reviews, ratings, reputation | references/workflows/review-analysis.md |
| SEO, SERP, crawl, content, RAG | references/workflows/content-and-seo.md |
| analytics, engagement, performance | references/workflows/social-media-analytics.md |
| trends, keywords, hashtags | references/workflows/trend-research.md |
| jobs, recruiting, candidates | references/workflows/job-market-and-recruitment.md |
| real estate, listings, hotels | references/workflows/real-estate-and-hospitality.md |
| price monitoring, e-commerce, products | references/workflows/ecommerce-price-monitoring.md |
| contact enrichment, email extraction | references/workflows/contact-enrichment.md |
| knowledge base, RAG, LLM data feed | references/workflows/knowledge-base-and-rag.md |
| company research, due diligence | references/workflows/company-research.md |
If no Actor matches in the index, search dynamically:
apify actors search "KEYWORDS" --json --limit 10 2>/dev/nullFrom results: items[].username/items[].name (Actor ID), items[].title, items[].stats.totalUsers30Days, items[].currentPricingInfo.pricingModel.
Step 2: Fetch Actor schema and check gotchas
Some Actors don't register an input schema with the platform (their schema lives in code). Try schema sources in this order — fall through on empty/error:
- Input schema (human-readable):
apify actors info "ACTOR_ID" --input 2>/dev/nullIf output is Error: No input schema found for this Actor, skip to source 2.
- Input schema (JSON keys only):
apify actors info "ACTOR_ID" --input --json 2>/dev/null | jq '.input.schema.properties // empty | keys'Empty result means no registered schema — fall through to source 3. To drill into a specific field:
apify actors info "ACTOR_ID" --input --json 2>/dev/null | jq '.input.schema.properties.FIELD_NAME'- README fallback (always works, contains usage examples):
apify actors info "ACTOR_ID" --readme 2>/dev/nullGrep the README for an "Input" / "Example input" section to copy the JSON shape.
- Last resort — call with minimal known input (e.g.
{"startUrls":[{"url":"..."}]}for crawlers) and let the Actor surface validation errors that reveal required fields. Seereferences/gotchas.mdfor known-good minimal inputs for common Actors.
Also read references/gotchas.md to check for common pitfalls and cost guardrails for the selected Actor.
Step 3: Configure and run
Skip user preferences for simple lookups (e.g., "Nike's follower count"). Go straight to running with quick answer mode.
For larger tasks, confirm output format (quick answer / CSV / JSON) and result count.
Before starting the run, double-check whether the task is short enough for a blocking call or should use the async pattern from Step 0.
Standard run (blocking):
apify actors call "ACTOR_ID" -i 'JSON_INPUT' --user-agent apify-claude-code-plugin/apify-ultimate-scraper --json 2>/dev/nullFrom output: .id (run ID), .status, .defaultDatasetId, .stats.durationMillis
Fetch results:
apify datasets get-items DATASET_ID --format jsonFor CSV: apify datasets get-items DATASET_ID --format csv
Quick answer mode: Fetch results as JSON, pick top 5, present formatted in chat.
Save to file: Fetch results, use Write tool to save as YYYY-MM-DD_descriptive-name.csv or .json.
Large/long-running scrapes:
apify actors start "ACTOR_ID" -i 'JSON_INPUT' --user-agent apify-claude-code-plugin/apify-ultimate-scraper --json 2>/dev/nullPoll: apify runs info RUN_ID --json (check .status for SUCCEEDED or FAILED).
Step 4: Deliver results
Report: result count, file location (if saved), key data fields, and links:
- Dataset:
https://console.apify.com/storage/datasets/DATASET_ID - Run:
https://console.apify.com/actors/runs/RUN_ID
For multi-step workflows: suggest the next pipeline step from the workflow guide.
Troubleshooting
Common errors and pitfalls are documented in references/gotchas.md. Read it before running PPE (pay-per-event) Actors.
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