Query and analyze YouTube sponsorship data using the `tl` CLI. Use this skill for finding channels, brands and sponsorships, and for data exploration, including counts, metrics, trends, time-series, distributions, single-record drill-downs, revenue / pipeline-weighting math, view-curve analysis, cross-source business questions. Examples: "How many deals did we close last quarter?", "What's the weighted pipeline by sales owner?", "Show me the view curve for video X", "Find mentions of Surfshark in transcripts", "Investigate this video", "Find channels...", "Find brands...".
Turn a sponsorship / sourcing goal into a structured, data-populated **Workflow** — an ordered funnel of report-stages that channels (or brands) move through, e.g. Sourced → Qualified → Get face on screen → Reach out → Contacted → Sold. Invoke when the user wants to build or set up a workflow or pipeline, design an outreach / acquisition funnel for a brand or campaign, turn an existing report into a workflow, or organise channel sourcing into stages. Triggers: "create a workflow", "build a pipeline / funnel", "set up outreach for <brand>", "turn this report into a workflow", "organise my sourcing into stages", "workflow for finding channels to sponsor <brand>", "build an acquisition funnel". It designs the funnel from the goal + the TL methodology, sources the entry stage with real data (delegating to tl-keyword-research / tl channels / tl recommender / guide-brand research), defines each stage as a query-or-list report, and creates it with "tl workflow create" (or, until the backend endpoint is deployed, han
Turn a topic into a *validated* content filter and the channels it selects. Invoke whenever the user wants to find videos or channels by what they are about — topics, concepts, niches, not IDs or names: "a group/set of keywords for <topic>", "keywords that represent <topic> content", "find content/channels about <topic>", "find investing channels" — or when you'd otherwise hand-compose a `tl db es` content search. It expands the topic into candidate keywords (with a gated web lookup for post-cutoff entities), probes Elasticsearch for each (counts + samples), validates matches against the user's stated intent, refines a boolean filter over ≥3 rounds, and delivers a keyword-group filter set + a clickable report link + the results the user chose: trend data at the video level (matching uploads + prevalence), or channel targets classified by topic intensity (core / recurring / one-off) and context-validated with cheap agents, or both. It ASKS which deliverable and which run mode (quick single pass vs deep ≥3-roun
Save the results of an in-chat data-exploration session as a TL report. Triggers when the user wants to persist a channels / brands / videos (uploads) / sponsorships list or filtered set they've been working with — phrases like "save this as a report", "save the list", "turn this into a campaign", "persist this", "make a report from what you found", "save the result", "I want to come back to this".
Detect non-organic views / fake engagement / bot comments on a YouTube channel before booking (or after delivering) a sponsorship. Use when asked to vet a channel, check if views/comments are real, investigate suspicious engagement, audit a sponsorship delivery, or whenever someone shares a YouTube channel/handle/URL and asks "is this real / safe to buy an ad on". Triggers: "fake views", "bot comments", "non-organic", "is this channel legit", "vet this channel", "engagement looks off", "audit this sponsorship".
External brand-user performance report. Ranks a brand's sponsorships by effective CPM once the sponsored videos went live, and compares live eCPM against the sold-date projection. Use whenever a brand user asks "which of my sponsorships performed best", "top partnerships this year", "best ROI deals", "effective CPM on my deals", "which sponsorships overperformed", "/top-partnerships", or any variation of "show me my best-performing sponsorships". This is the brand-side equivalent of internal performance reporting — fire it eagerly any time a brand wants to look back at their booked deals through a performance lens, even if they don't say the words "CPM" or "eCPM".
Calculate the optimal views guarantee (VG) for a multi-video sponsorship buy with a YouTube creator. Given a channel ID or name, returns "video bundle size / views guarantee / likelihood to hit" based on bootstrap simulation of the channel's recent video performance (view counts measured at video age ~30 days). Use when someone asks "what VG should I push for with [creator]", "how many videos should I buy from [creator]", "calculate VG for [channel]", "what's a safe guarantee for [channel]", or anything involving setting views guarantees in a sponsorship deal. Triggers on "VG", "views guarantee", "views minimum", and any request to size a multi-video buy.