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 Frontal-so/outbound-skills --skill people-enrichmentgit clone --depth 1 https://github.com/Frontal-so/outbound-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/frontal-so/outbound-skills/people-enrichment)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/people-enrichment"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/people-enrichment/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/frontal-so/outbound-skills/people-enrichment"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/people-enrichment.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 | $0.00110 | $0.00981 |
| Opus 5 | $0.00055 | $0.00491 |
| Sonnet 5 | $0.00022 | $0.00196 |
| Haiku 4.5 | $0.00011 | $0.00098 |
Grade A, and why
people-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 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
People Enrichment
You help users find and enrich contacts at target companies using Clay's people search and LinkedIn enrichment capabilities.
References
- Read
{SKILL_BASE}/resources/core-concepts.mdfor Clay table fundamentals. - Read
{SKILL_BASE}/resources/workflow-patterns.mdfor lead sourcing patterns and data import methods.
People Discovery Workflow
Company List (with domains)
|
Find People (by title + seniority)
|
LinkedIn Enrichment (profile data)
|
Filter (ICP match)
|
Email/Phone Waterfall (separate sub-skills)
Best Sources for Finding People
- LinkedIn Sales Navigator -- most accurate for B2B, filter by title/seniority/company
- Apollo Find People -- large database, good coverage, 2-3 credits
- Clay Find People -- native Clay search across multiple providers
- CRM Import -- pull existing contacts from HubSpot/Salesforce
Key Filtering Criteria
- Title keywords: VP, Director, Head of, Manager, Chief, C-level
- Seniority levels: C-Suite, VP, Director, Manager
- Department: Sales, Marketing, Engineering, Finance, Operations
- Recent hires: joined in last 90 days (high intent signal)
- Limit: 3-5 decision makers per company (avoid over-enrichment)
Setup Steps
- Start with a company table that has domains or LinkedIn company URLs
- Add "Find People" enrichment -- specify title keywords and seniority
- Map company domain or LinkedIn company URL as input
- Set limit to 3-5 contacts per company
- Add LinkedIn Profile enrichment for each found person
- Filter by ICP fit using formulas or AI column
- Proceed to email/phone waterfall (separate sub-skills)
LinkedIn Enrichment Data Points
| Data Point | Source | Notes |
|---|---|---|
| Full name | LinkedIn Profile | Auto-split into first/last |
| Current title | LinkedIn Profile | Most accurate source |
| Seniority | LinkedIn Profile | C-Suite, VP, Director, etc. |
| Location | LinkedIn Profile | City, state, country |
| Tenure | LinkedIn Profile | Time at current company |
| Past companies | LinkedIn Profile | Career history |
| Skills | LinkedIn Profile | For personalization |
| Connections | LinkedIn Profile | Network size indicator |
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 · 88 lines · 110 tokens per session scan A 9f64495b9f45
people-enrichment is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 2mo ago), licensed MIT. It adds 110 tokens to every session and 981 once invoked, about $0.0006 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.
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