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Generate an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.

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The phone is your last API. Give your agent a voice to call any US business and take action in the real world. PlaceCall handles reservations, inquiries, and quotes - navigating IVRs, holds, and transfers. You get a verified outcome + full transcript. First 250 calls free. Pay only for outcomes.

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Fetch the transcript of a YouTube video as text or JSON.

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Build AI audio transcription systems. TRIGGERS - Use when user needs help with ai-audio-transcriber related tasks.

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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Debug and troubleshoot ElevenLabs conversational AI agents and Twilio calls. Use when diagnosing agent issues, analyzing failed calls, troubleshooting audio problems, investigating conversation breakdowns, reviewing error logs, or optimizing underperforming agents. Includes transcript analysis, error diagnosis, and performance troubleshooting.

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Use for local Granola archive search, sync freshness, notes/transcripts/panels, Markdown export, snapshots, Keychain-safe source debugging, and Graincrawl repo/release work.

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"Summarize and analyze earnings calls (法說會) including financial highlights, management commentary, guidance, and analyst Q&A key takeaways. Use this skill when the user needs to digest an earnings call transcript, extract key financial data and forward guidance, compare actual results vs consensus estimates, or prepare for an investor meeting — even if they say 'summarize this earnings call', 'what did management say about next quarter', 'did they beat estimates', or 'key takeaways from the 法說會'.".

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Prepare for a sales call with account context, attendee research, and suggested agenda. Works standalone with user input and web research, supercharged when you connect your CRM, email, chat, or transcripts. Trigger with "prep me for my call with [company]", "I'm meeting with [company] prep me", "call prep [company]", or "get me ready for [meeting]".

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Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).

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Turn long footage (podcast, interview, stream, recording) into ready-to-post vertical shorts. Use when the user points at a long video and wants short clips — "cut this into shorts", "make clips from this recording", "turn this podcast into verticals". Needs the NanoClip CLI (analysis) and HyperFrames (rendering). NOT for editing an existing short, generating footage, or plain transcription.

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Turn meeting notes, transcripts, or rough bullets into decisions, action items, owners, due dates, and follow-up queues. Use when the work is repetitive meeting cleanup or recap writing. Do not use for negotiation strategy, legal advice, or executive decision framing.

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Summarize meeting notes or transcripts into decisions, action items, owners, risks, and follow-up messages. Use after meetings when raw notes need a clean recap.

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Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization

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Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation, audio transcription, translation, summarization, and Inference Endpoints

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Ingest one new source into an existing persistent markdown wiki or established vault workflow. Use this when the user asks to add an article, PDF, note, URL, transcript, or other source into their wiki and wants the source filed, linked, indexed, and logged. If the wiki workflow does not exist yet, use $wiki-bootstrap first. This skill is for the ingest operation only.

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Transcribe audio files locally with Interpreter's builtin-transcribe tool server. Use when a user asks to transcribe speech from recordings without cloud transcription or API keys.

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Clones a VIDEO ad end to end for a different product or offer, on the Novoads API. The deliverable is a finished rendered MP4 — the WHOLE ad, not its opening, and not a template. Reads the source's style, pacing, camera work, dialogue and tone, adapts it into a Seedance 2.0 prompt, prices it, renders it, files the source beside the clones and diffs each clip's transcript against the approved script. Use for "clone this video ad", "recreate this video for my brand", "make this ad but for my product" when the source is a video, "clone my competitors' VIDEO ads", or a video ad handed over with a product photo. **Among cloners the source's medium decides, not the wording**: "clone this ad" plus a video lands here; a still, or nothing attached, is clone-image-ad, and animating a still as-is is image-to-motion. This pack has no hook-only skill: for the opening alone, clone the whole ad and cut. If it does not move, wrong skill.

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Use when the user wants their way of working with Claude assessed — "review my session", "how am I using Claude Code", "audit my setup / workflow", "am I following best practices", "coach me", "what should I improve" — or pastes a Claude.ai/Cowork/Tag transcript and asks how they could have worked better. Do NOT use for reviewing code changes (that is code review) or for teaching a product from scratch (use academy-learn); this skill only reviews how the human works with Claude.

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Use when a task needs the judgment of a Court Reporter — producing a realtime or CART feed during a deposition or trial, triaging a QC pass on a draft transcript before certification, drafting or applying an errata sheet under FRCP 30(e), reading back testimony from steno notes on a judge's request, or handling a sealed-record or in-camera confidentiality flag.

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Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.

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Execute ENCODE RNA-seq pipeline from FASTQ to gene quantification and signal tracks. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing RNA-seq data with STAR alignment, RSEM/Kallisto quantification, or generating expression matrices. Trigger on: RNA-seq pipeline, gene expression, STAR alignment, RSEM quantification, transcript quantification, TPM, FPKM, RNA processing, run RNA-seq.

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Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell data.

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Guide for using JASPAR transcription factor binding profiles with ENCODE ChIP-seq data. Use when users need to find TF binding motifs in ENCODE peaks, validate ChIP-seq targets with known motifs, or scan regulatory regions for TF binding potential. Trigger on: JASPAR, motif database, binding profile, PWM, position weight matrix, TF motif, motif enrichment, motif scanning, binding site prediction.

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