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 agentmods add skills/scraperapi/scraperapi-skills/scraperapi-lead-enrichmentnpx skills add scraperapi/scraperapi-skills --skill scraperapi-lead-enrichmentgit clone --depth 1 https://github.com/scraperapi/scraperapi-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/scraperapi/scraperapi-skills/scraperapi-lead-enrichment)<a href="https://agentmods.dev/skills/scraperapi/scraperapi-skills/scraperapi-lead-enrichment"><img src="https://agentmods.dev/badge/skills/scraperapi/scraperapi-skills/scraperapi-lead-enrichment.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 | $0.00210 | $0.02024 |
| Opus 5 | $0.00105 | $0.01012 |
| Sonnet 5 | $0.00042 | $0.00405 |
| Haiku 4.5 | $0.00021 | $0.00202 |
Grade A, and why
scraperapi-lead-enrichment 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 4d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Enrichment
Given any seed information about a person or company, call ScraperAPI directly to search the web and fetch relevant pages, then synthesize everything into a structured contact card.
You — Claude — execute the API calls using the ScraperAPI MCP tools. Do not generate code for the user; run the searches yourself and report findings as you go.
Phase 1 — Analyze the Seed
Before running any searches, state clearly what you already know and what you're looking for. Categorize the seed:
| Seed type | Information gaps to fill |
|---|---|
| Person name (+ optional company) | Title, email, phone, location, company details |
| Company name | Website, description, size, funding, contact info |
| Profile URL (LinkedIn, Crunchbase, etc.) | Fetch directly; then fill remaining gaps |
| Email address | Owner name, company, company details |
| Domain / website | Company info, key contacts, funding |
Announce before searching: "Starting with: [what I have]. Will search for: [what's missing]."
Phase 2 — Discovery Searches
Run searches by what you're looking for, not by which site to target. Google will surface whatever sources exist — company website, Crunchbase, Wikipedia, news, directories, LinkedIn, G2, etc. Collect all promising URLs from organic_results[].link and carry them into Phase 3.
Search tool: Call mcp__ScraperAPI__google_search with query, num: 10, and countryCode: "us". Read snippets carefully — they often contain the data you need without an extra fetch.
2a. Person name as seed
-
Profile and context Query:
"PERSON_NAME"+"COMPANY_NAME"Surfaces: personal website, bios, speaker profiles, press mentions, social profiles, company team pages. -
Contact info Query:
"PERSON_NAME"+"COMPANY_NAME"+contact+emailSurfaces: email addresses, contact pages, directory listings.
Then run 2b with the company name.
2b. Company name as seed (or company found in 2a)
What ships with it
2 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.
- 4d ago First seen · 166 lines · 210 tokens per session scan A 6090f8884e4a
scraperapi-lead-enrichment is a skill published in the GitHub repository scraperapi/scraperapi-skills (10 stars, last pushed 27d ago), licensed MIT. It adds 210 tokens to every session and 2,024 once invoked, about $0.0011 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 2026-08-31.
Other skills, from other repositories
investigate-issue
Investigate a GitHub issue by fetching details, analyzing the codebase, researching documentation, and presenting an actionable implementation plan with test guidance. Use when asked to investigate, analyze, triage, or plan work for a GitHub issue. Invoked with /investigate-issue or /investigate-issue (prompts for ID).
resolve-pr-comments-stack
Resolve unresolved PR review comments across an entire Graphite (gt) stack of many PRs, bottom-up, in one working directory. Use when asked to "go through this stack and resolve comments", "clean up review comments across the whole stack", or given a list/range of PR numbers that form (or partially form) a gt stack.…
resolve-pr-comments
Skill "resolve-pr-comments" from maximhq/bifrost, covering resolve pr comments, usage, workflow overview, step 1: detect repository and step 2: fetch unresolved comments (graphql).
harness-test-writer
Add regression test cases to the Bifrost provider harness (the Postman collection run via make run-provider-harness-test) based on a merged PR or a GitHub issue. Fetches the PR/issue, traces the affected wire path in the codebase, checks existing harness coverage, designs cases following harness conventions, inserts…
review-pr
Reviews a PR or diff with multi-angle finders and adversarial verification, then reports a findings table, a merge/no-merge recommendation, required followups, and offers to create a follow-up PR. Use when the user types /review-pr [PR# | branch | path].
surf
Use when the user wants crypto data — token prices, on-chain SQL, prediction-market positions, CEX order books, wallet labels/net-worth, social mindshare, news, or unified search. 83 endpoints across exchange, on-chain, wallet, social, prediction, news and search — one API, flat $0.0085/call in USDC via x402. Settles…