Skills your AI team can install today
104 signed skills and professions from 4 vendors, with 1 video and 52 articles. Read any page free; a free account downloads them.
Skill4 imagesThumbnail
@di-atomic · Media
The click image for a video, graded where it is shown smallest. For a YouTube video it plans a 2-3 variant A/B set that differs in concept, not colour: one named axis and one hypothesis per variant, the brand's own face as the render reference. For a Short, Reel or TikTok it makes one cover. For any video it picks the frame that should be frame 0 and hands it to @di-atomic/video-editor. Three gates print PASS/FAIL with numbers: headline height in arcminutes at the 200 px YouTube sidebar and the 129 px Instagram grid, contrast, the duration-badge corner and the Shorts overlays, and whether AI-drawn words say what was asked. A host without OCR gets UNVERIFIED, never PASS. 5 recipes, 37 registry items, 5 reference procedures. guidance-only (nested skills:[{id,schema}] with discovery-only methods + peer_dependencies) — agents reach it via skill_read.
Skill5 imagesVideo Researcher
@di-atomic · Data Collection
Two research jobs for a video team. Mode 1 watches the market: every week it scores each video on a declared set of channels against that channel's own age-matched median, tests each theme against the rest of the channel's videos, and drops ranked idea cards on a Research board, each carrying the video, the metric and when it was measured. Mode 2 reads the product: it reads the released code, not the marketing page, and returns a fact sheet where every claim cites a file and a line. EN, DE and DA. Cron runs the scan, a heartbeat catches a missed week. Four verifiers print PASS or FAIL with numbers. guidance-only (nested skills:[{id,schema}] with discovery-only methods + peer_dependencies) — agents reach it via skill_read.
Skill4 imagesVideo Analyst
@di-atomic · Media
Watch a video, emit a reusable TEMPLATE — not a summary. Takes a YouTube link or a local file, measures what a script can measure (speech timing and pace, shot changes, the opening seconds, token cost), has the host agent's own model judge only what needs eyes (sections, the kind of hook, what is on screen), and aggregates many videos of one type into a template the video-director fills instead of inventing structure. Every number is tagged measured, platform or judged; cut rhythm is only cited after an audit; a template's strength follows its sample size. Five gates print PASS/FAIL with numbers. guidance-only (nested skills:[{id,schema}] with discovery-only methods + peer_dependencies) — agents reach it via skill_read.