2,381 skills found ¡ Page 34 of 80
davepoon / implement-featureImplements a feature from its specification. Reads the spec, designs architecture, writes code and tests. Delegates to the Forja (Dev) agent.
davepoon / review-findingsAddresses and fixes findings from a QA code review. Reads the review report, fixes critical and warning issues, and prepares for re-verification. Delegates to the Forja (Dev) agent.
davepoon / uctm-initInitialize uc-taskmanager for the current project. Creates works/ directory and configures Bash permissions in .claude/settings.local.json
davepoon / work-pipelineTriggers the WORK-PIPELINE when a user request starts with a [] tag (e.g., [new-feature], [bugfix], [WORK start]). Use this skill whenever you detect a [] tag at the beginning of a user message.
davepoon / email-marketing-bibleData-backed email marketing skill for AI agents
davepoon / ontoly-software-graphUse Ontoly's deterministic Software Graph and MCP server for codebase architecture, request tracing, dependency analysis, and impact analysis.
charlie947 / quote-postTwo-step workflow for creating quote posts on LinkedIn. The assistant drafts original short quotes to accompany a caption, then produces a Gemini prompt that recreates a reference image with the chosen quote baked in.
charlie947 / youtube-thumbnailGenerate a branded YouTube thumbnail from a video title. Uses a reference photo of the creator, high-CTR thumbnail principles, and brand colours to produce a ready-to-generate image prompt for Gemini.
axtonliu / mermaid-visualizerTransform text content into professional Mermaid diagrams for presentations and documentation
ericosiu / podcast-pipelinePodcast-to-Everything content pipeline. Takes a podcast RSS feed or raw transcript and generates a full cross-platform content calendar: short-form video clips, Twitter/X threads, LinkedIn articles, newsletter sections, quote cards, blog outlines with SEO keywords, and YouTube Shorts/TikTok scripts.âĻ
ericosiu / show-and-tell-video-slateTurn authorized current builds, workflows, dashboards, analytics, and completed work into proof-led founder videos, then rank and combine the strongest filmable artifacts into exact 15-minute long-form slates with strict title and thumbnail evaluation
ericosiu / lead-dossiername: lead-dossier description: > Multi-source account research, cascade enrichment, and lead pipeline. Combines website scraping, tech stack detection, CRM enrichment, hiring/news signals into structured dossiers. Includes full lead sourcing pipeline: search â verify â dedupe â upload.
ericosiu / net-new-video-editorTurn newly recorded talking-head footage into review-ready vertical video drafts with an explicit edit plan, deterministic FFmpeg rendering, captions, hook cards, audio normalization, and visual QA.
ericosiu / video-clip-pipelineAI-powered pipeline that converts long-form YouTube episodes into standalone highlight clips. Download â Transcribe â AI Segment â Cut â Upload. A 60-minute episode becomes 3â5 clips in ~15 minutes.
ericosiu / sales-pipelineComplete AI-powered sales pipeline automation: website visitor identification â intent scoring â suppression â campaign routing â dead deal resurrection â trigger prospecting â self-learning ICP optimization.
ericosiu / short-form-pipelineExtract viral short-form clips (TikTok, Reels, Shorts) from long-form YouTube videos. Handles download, transcription, AI segmentation, cutting, vertical cropping, and caption burn-in.
ericosiu / team-opsAI-powered team performance analysis and meeting intelligence: ruthless performance audits using the "Elon Algorithm" + automatic extraction of action items, decisions, and follow-ups from meeting transcripts.
ericosiu / closed-loop-analytics-upgradeUpgrade marketing, content, SEO/AEO/GEO, and revenue skills so changes are judged by platform analytics instead of vibes
rebelytics / one-skill-to-rule-them-allThe meta-skill that builds and improves all your skills, including itself. Watches your work sessions (autonomous or human-led), captures patterns, corrections and judgement calls, and turns them into skill improvements and new skill candidates for your review.
jordan-gibbs / deep-researchDeep research with hyperresearch, for Claude Code and OpenAI Codex
Ar9av / wiki-dedupDetect and merge wiki pages representing the same concept under different names. Use for page-identity deduplication and consolidation. Destructive merges require confirmation; not for link repair or general linting.
Ar9av / daily-updateRun or configure the daily wiki maintenance cycle: check source freshness, refresh the index and hot.md, and manage its scheduled 9 AM launchd/systemd/cron reminder. Use for daily or morning wiki refresh or scheduler setup and verification.
Ar9av / cross-linkerFind and add missing cross-references between wiki pages
Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence.
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis.
Property-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains.
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR
Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling.