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get-qualified-leads-from-luma

get-qualified-leads-from-luma is a skill for Claude Code, Codex from gooseworks-ai/gooseworks-skills. It costs 108 tokens per session (2,563 once invoked), scanned B, original, no licence file.

An event-based lead prospecting workflow that finds Luma events by topic and location, reviews attendees and hosts, and identifies people who match your criteria.

In plain words
What is it for?
Use it to discover and qualify potential customers from Luma event audiences, then share the results with a sales or marketing team.
Why use it?
It removes the manual work of finding relevant events, checking participants, and sorting potential leads. Results go to a Google Sheet, with a Slack alert for the highest-priority leads.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

not rated 12repo 7mo ago B scan 108 tokens no licence

Good fit Use it to discover and qualify potential customers from Luma event audiences, then share the results with a sales or marketing team.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma
View source ↗ gooseworks-ai/gooseworks-skills
Install

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.

Any agent
npx skills add gooseworks-ai/gooseworks-skills --skill get-qualified-leads-from-luma
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/gooseworks-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for get-qualified-leads-from-luma

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma/github.svg)](https://agentmods.dev/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma/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.

agentmods 80×15 button for get-qualified-leads-from-luma

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/gooseworks-skills/get-qualified-leads-from-luma.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 108 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,563 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00108 $0.02563
Opus 5.5 $0.00043 $0.01025
Sonnet 5.5 $0.00022 $0.00513
Haiku 4.5 $0.00011 $0.00256

Measured 2mo ago against content hash 5b4b6690a8d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

get-qualified-leads-from-luma scanned grade B with 2 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 2mo 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

curl -X POST -H 'Content-Type: application/json' -d '{"text":"test"}' YOUR_WEBHOOK_URL

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Use Python with `urllib.request` to POST to the webhook:
skills/composites/get-qualified-leads-from-luma/SKILL.md · 248 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

1 file 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.

Changes

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.

  1. 2mo ago First seen · 248 lines · 108 tokens per session scan B 5b4b6690a8d4

Subscribe to this mod's changes

get-qualified-leads-from-luma is a skill published in the GitHub repository gooseworks-ai/gooseworks-skills (12 stars, last pushed 7mo ago), with no licence file. It adds 108 tokens to every session and 2,563 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Marketing and SEOResearchlead-generation
Related

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