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Found 79 Skills
MANDATORY recipe for every Caffeine build that lists, reads, creates, shares, or organizes files and folders on the user's own Google Drive. The ONLY supported path is the `googledrive-client` mops package (Drive REST API v3) combined with the `google-oauth` mops package (OAuth 2.0 token exchange + refresh + PKCE). Hand-rolling `ic.http_request` calls to `oauth2.googleapis.com` or `www.googleapis.com/drive/v3` is a FORBIDDEN anti-pattern — it bypasses bearer auth, the `is_replicated = ?false` replication-cost safeguard, and the `google-oauth` library's token handling. Load this skill ONLY when the user, spec, or a prior task refers to **Google Drive specifically** — e.g. "Google Drive", "my Drive", "Drive files/folders", a Drive file/folder ID or share link, "upload to Google Drive", "list my Drive files", or Drive sharing/permissions. Do NOT load it for generic file storage, documents, uploads, or access-control features that are not Google Drive — those are unrelated and this connector must not be attached to them. When it does apply, load it BEFORE writing any code that touches a Google endpoint.
Plan or execute a replication of a paper, claim, or benchmark. Use when the user asks to replicate results, reproduce an experiment, verify a claim empirically, or build a replication package.
MANDATORY recipe for every Caffeine build that reads Spotify catalog data or drives a user's Spotify account from a canister. The supported path is the `spotify-client` mops package (Spotify Web API) over outbound HTTPS with an OAuth 2.0 bearer token minted off-chain. Hand-rolling `ic.http_request` calls to `api.spotify.com` is a FORBIDDEN anti-pattern — it bypasses the non-replicated-outcall safeguard (player state and `progress_ms` differ per node and fail consensus), the generated JSON decoding, and the bearer handling. Load this skill whenever the user, spec, or any prior task mentions Spotify, a song, track, artist, album, playlist, music search, new releases, genres, markets, "what's playing", recently played, the queue, player controls (play / pause / skip / shuffle / repeat), a saved library, podcasts (shows or episodes), chapters or audiobooks — and BEFORE writing any code that touches a Spotify endpoint.
Verify a research claim or academic citation by tracing it through publication → methodology → raw data → independent replication. Routes through perplexity-research for the actual web lookup, then formats results as a citation-checked brain page. Use when a book/article/conversation cites a study and you want to confirm the claim is real, replicated, and accurately characterized.
Design customer-facing SQL access to a product's data - a JDBC/ODBC endpoint, warehouse share, or hosted query surface. Covers the architecture gate by scan frequency (zero-copy share, replicated copy, per-tenant compute isolation), engine-level tenant isolation with secure views and row-level security, an additive-only schema-stability contract enforced in CI, BI-tool connectivity and driver certification, query governance and cost caps, short-lived credential issuance, and the pricing shape. Use whenever the user mentions JDBC, ODBC, SQL access for customers, connecting Tableau or Power BI to product data, or pricing a SQL add-on - even if they never say "SQL access". Do NOT use for bulk file delivery - use samber/developer-platform-skills@bulk-data-sharing-design instead.
Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.
Roblox project structure and client/server model - replication, where code and assets belong (ServerScriptService, ReplicatedStorage, StarterPlayer), RunContext, service/controller bootstrapping, player/character lifecycle, CollectionService components, attributes, streaming-safe client code, library choices. Use when starting a project, deciding where code goes, or fixing replication/streaming bugs.
Prepares a reproducibility artifact (code/data) for submission and badging. Use when a researcher says "artifact evaluation", "artifact appendix", "reproducibility", "badge", "Artifacts Available/Evaluated/Functional/Reusable", "Results Reproduced/Replicated", "ACM badging", "USENIX/OSDI/SOSP AE", "SIGMOD ARI", "NeurIPS code/checklist", "ACL repro checklist", "Zenodo DOI", "Software Heritage", "anonymize my code/repo", or "package my code". Builds the artifact README + appendix, the dependency/run instructions, an anonymized repo for double-blind, and archival-DOI (Zenodo version vs concept) / Software Heritage SWHID guidance; resolves the ACM badge taxonomy and the Reproduced/Replicated era swap; and lints the artifact directory against the ML Code Completeness checklist with bundled stdlib-only scripts. Outputs an artifact-readiness checklist + packaging plan. Re-verifies the venue current artifact rules live. Advisory only; never submits.
Replicate the macbook-metrics setup on any Mac — a local, always-on system-metrics collector (CPU, GPU, RAM, disk, network, battery, thermals) built as a Swift CLI, run by launchd every 60s, stored in SQLite, and backed up to a private GitHub repo. Use when someone wants long-term Mac performance tracking, asks how macbook-metrics works, or wants to set up the same monitoring on a new machine. Differentiator: covers the full architecture and setup ideology, not day-to-day querying of an existing install.
MANDATORY recipe for every Caffeine build that posts to X (Twitter) from a canister. The supported path is the `x-client` mops package (X API v2) over outbound HTTPS, with per-user OAuth 2.0 (PKCE, no client secret). Hand-rolling `ic.http_request` calls to `api.x.com` is a FORBIDDEN anti-pattern — it bypasses bearer auth, the non-replicated-outcall safeguard, and the package's null-field JSON handling. Load this skill whenever the user, spec, or any prior task mentions posting a tweet, "tweet this", X/Twitter, sharing to X, or any equivalent phrasing — and BEFORE writing any code that touches an X endpoint.
Reverse-engineer and rebuild any website — including its WebGL/WebGPU/canvas shader effects — into a clean local codebase. Use this whenever the user wants to clone, replicate, rebuild, reverse-engineer, or copy a website or landing page, especially designy sites with animated/shader/3D hero backgrounds. This is the top-level coordinator: it does recon, classifies every page surface as DOM vs GPU-rendered, routes plain layout to the dom-clone sub-skill and shader surfaces to the shader-extract sub-skill, scaffolds a build target on demand, composites the two tracks, and runs automated visual QA. It also produces a human-readable TEARDOWN.md (stack, measured design system, every effect with its exact runtime params and how it works) — pass --analyze-only to stop there. Trigger on "clone this site", "rebuild this page", "make a copy of this website", "reverse-engineer this landing page", "clone this but the background is some WebGL thing", any pixel-accurate site reproduction, AND on analysis asks: "how did they build this", "tear down this site", "site teardown", "break down this page", "what stack/animations does this site use", "how does this effect work", "website blueprint", "steal this website's design", "/site-teardown". Provide one or more target URLs.
Build Celigo syncs (Celigo Data Ingestion) -- managed pipelines that replicate many tables from a source application into a data warehouse, with a historical backfill, incremental runs and schema-drift handling. Covers sync versus flow, the sync integration, datasets, destinations, the enable and license gates, runs and resyncs, and sync jobs, errors and events. Use when replicating application data into Snowflake, Google BigQuery, Microsoft SQL Server or NetSuite Analytics Warehouse, or when building, running or troubleshooting a sync.