Acquisition and launches
Conference pipeline
Turn useful event conversations into consent-aware, qualified next steps and bounded evaluations.
Open-source skill · format validated
When this is useful
Plan conference and event lead generation for developer tools and data products: audience fit, meetings, useful demos, consent-aware capture, qualification, and follow-up. Use for event pipeline and conference sales content; not bulk attendee scraping or automatic outreach.
What to bring
Event and audience, product task, participation format, owner capacity, budget ceiling, available demo, and outreach permissions.
What you can work toward
A before/during/after plan, demo brief, conversation prompts, capture schema, follow-up drafts, ownership, and measurement definitions.
Developer-tool version
Use a reproducible engineering demo with a safe offline fallback. Qualify stack, recurring task, and team-integration ownership. Capture only permitted notes and an agreed next step; badge scans are not qualified pipeline or blanket outreach consent.
Data-product version
Use synthetic records and a workload-evaluation worksheet. Qualify source/destination, correctness/freshness need, access owner, and platform approval without collecting sensitive data. Track agreed evaluations separately from scans and conversations.
How to use it
Choose the version for your product type and follow its repository installation instructions. Keep the skill folder, references and any assets together. Each skill works on its own; reuse a shared brief when helpful rather than repeating a full intake.
The source follows the open Agent Skills format and is MIT licensed. Live research and execution depend on the tools and permissions available in your host. Preparing a plan or draft does not itself authorize publishing, messaging, spending or production changes.
A starting prompt
Use the conference pipeline skill for our developer tool or data product. Our task is [specific task], our supported environment is [environment], and the decision is [decision]. Use these facts and sources: [evidence]. Produce the requested artifact, label unknowns, and do not invent results or perform external actions beyond my authorization.
How to judge the result
Do not scrape restricted attendee data, send unapproved messages, or report every scan as pipeline. Separate preparation from paid sponsorship or outreach execution.
Check that the product-specific version changes the recommendation, the requested deliverable is complete, and proposed tests are distinguished from observed results. Format validation does not establish how a model will perform on your product.
From input to reviewed output
Put it to work
- Choose the collection for your product type and install the relevant skill with its bundled references and assets.
- Supply the task, supported behavior, existing evidence and constraints that affect the decision. Reuse context already available.
- Ask for the concrete deliverable, distinguishing facts, hypotheses, unknowns and any untested instructions.
- Check the product-specific acceptance criteria, source claims and next steps before using or publishing the output.
Limits and tradeoffs
Do not scrape restricted attendee data, send unapproved messages, or report every scan as pipeline. Separate preparation from paid sponsorship or outreach execution. No fresh-host model performance is claimed; verify output against your product, evidence and authorized environment.