Skill UI

Prepare an AI outbound phone call end-to-end: research the callee, define the objective and fallback, draft a natural branching script with guardrails, and generate a post-call summary template.

Runs Cantera homogeneous ideal-gas reactors for constant-volume or constant-pressure ignition, computes temperature-based ignition delay, checks conservation, and refines numerical settings with mechanism provenance.

This tool validates AI agent changes by running statistical regression tests to ensure performance doesn't degrade. It grades tool trajectories, detects flaky cases, and integrates with CI to block merges when significant regressions occur. Supports pass@k metrics and paired statistics for reliable evaluation.

This skill enables users to generate AI audiobooks from manuscripts or course text using the Beatra service. It supports voice cloning and text-to-speech narration. The package is pinned and verified for security. Users must authorize access before use. It works within Claude Code environments.

Routes marketing and GTM decisions into AI-primary, collaborative, and human-primary governance zones by reversibility, exposure, and frequency, so teams know which AI outputs need human review and which agents may own.

Enhance AI-generated portraits, product images, and marketing visuals by fixing plastic skin, malformed hands and faces, repeated textures, and inconsistent lighting. Works with Claude Code, Codex, and OpenClaw via paid Beatra service. Requires explicit user approval for paid operations.

Generate practical shot lists and one to four storyboard key-frame images from a script, scene, or ad brief via the paid Beatra hosted service, directly inside Claude Code, Codex, or OpenClaw.

Turn YouTube videos, channels, or playlists into text using the Apify youtube-transcript-scraper Actor. Get plain text, timestamped segments, SRT/VTT captions, and translated transcripts with video metadata for summaries, quotations, and research.

This skill executes a single iteration of an automated research experiment. It reviews historical results, decides on a specific code modification, edits the target file, commits changes via git, and evaluates the outcome. Users can specify an experiment or select from a list. The process ensures only one change is made per iteration to isolate variables, preventing evaluation script modification. It supports strategy escalation based on run count and reports keep, discard, or crash status.

Measure a dataset's detection floor before interpreting any trading-signal backtest. Pre-registers every trial in an append-only registry, adjusts for multiple testing, and reports effects below the floor as UNDECIDABLE rather than 'no effect'.

Provides step-by-step guidance for deploying the Categraf collector on Linux, Docker, Windows, and Kubernetes. Covers installation, config.toml writers and heartbeat setup, systemd service registration, and verification commands.

Runs reproducible CellProfiler pipelines for nuclear segmentation, cell counting, and per-object fluorescence measurements on 2D microscopy TIFF images, including batch execution, overlays, and QC.