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 apify/awesome-skills --skill apify-google-maps-leadsgit clone --depth 1 https://github.com/apify/awesome-skillsWrote 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/apify/awesome-skills/apify-google-maps-leads)<a href="https://agentmods.dev/skills/apify/awesome-skills/apify-google-maps-leads"><img src="https://agentmods.dev/badge/skills/apify/awesome-skills/apify-google-maps-leads/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/apify/awesome-skills/apify-google-maps-leads"><img src="https://agentmods.dev/badge/skills/apify/awesome-skills/apify-google-maps-leads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.03855 |
| Opus 5 | $0.00000 | $0.01928 |
| Sonnet 5 | $0.00000 | $0.00771 |
| Haiku 4.5 | $0.00000 | $0.00385 |
Grade A, and why
apify-google-maps-leads 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 10d 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Maps Leads (with Scalelist backfill)
Build a lead CSV from Google Maps in one pipeline:
- Interview — ask target audience, target geography, and whether to use reviews for lead scoring.
- Scrape — one
compass/crawler-google-placesrun with four add-ons pre-configured (leads enrichment, website contacts, Instagram + Facebook profiles, optional reviews). - Filter & score — apply a review-based score if scoring is on.
- Discover missing names — for places that came back with zero (or unnamed) leads, call
apify/ai-web-scraperon the business website to extract owner/decision-maker names. Scalelist can't work without a name. - Backfill contacts — call
scalelist/phone-finderfor leads with a missing phone,scalelist/email-finderfor leads with a missing email. - Deliver — a deduplicated CSV plus a
run_metadata.jsonsidecar.
Prerequisites
- Apify account (sign up)
- Auth via one of:
apify login(OAuth, if using the Apify CLI)APIFY_TOKENenv var- Token from Apify Console → Settings → Integrations
Either the Apify CLI (recommended for portability) or the Apify MCP connector works. Commands below use the CLI; the MCP path is a drop-in via the call-actor and get-dataset-items tools.
Workflow
Track progress with this checklist:
Task Progress:
- [ ] Step 1: Interview — audience, geography, scoring choice
- [ ] Step 2: Build the Google Maps input
- [ ] Step 3: Run compass/crawler-google-places
- [ ] Step 4: Filter + score (if scoring enabled)
- [ ] Step 5: Discover missing names via apify/ai-web-scraper
- [ ] Step 6: Backfill missing phones and emails via scalelist Actors
- [ ] Step 7: Deduplicate and render the CSV
Step 1: Interview
Ask three questions as one block — don't drip them one by one.
- Target audience — the business type(s) to search for. Free text. Examples:
"dentists","vegan restaurants","boutique hotels","dog groomers, pet stores"(comma-splittable → array). - Target geography — one location per run. City + country reads best (
"Berlin, Germany","Austin, TX"). If the user gives a country only, warn that Maps runs perform best on city-scoped searches. - Use reviews for lead scoring? (y/n) — if yes, we pull reviews (
maxReviews) and filter by review volume + star rating post-run. If no, we skip reviews to cut cost.
What ships with it
5 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.
- 10d ago First seen · 238 lines · 0 tokens per session scan A 062459d7b4ab
apify-google-maps-leads is a skill published in the GitHub repository apify/awesome-skills (249 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,855 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 2026-08-30.
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