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Found 5,507 Skills
Supernormal platform help — AI agent for agencies that turns meeting context into deliverables (pitch decks, briefs, emails, spreadsheets). Use when setting up Supernormal desktop app for bot-free recording, Supernormal AI agents not generating deliverables, Supernormal credits running out or credit system confusion, Supernormal bot joining Zoom calls uninvited, comparing Supernormal to Sembly or Fathom or Fireflies for agency work, Supernormal MCP integration, Supernormal Slack or CRM sync to HubSpot or Salesforce, or Supernormal transcription accuracy issues with accents. Do NOT use for choosing between AI note-takers (use /sales-note-taker) or general meeting transcript API integration (use /sales-note-taker).
Enforce IPPF/UNFPA/UNAIDS publication-standard citations on MEL/SRHR output. Use whenever Ane produces a theory of change, evaluation design, indicator set, donor report, or SRHR programme analysis. Injects current authoritative framework versions with author and year, flags outdated versions, and applies the data-gap protocol. Do not use for non-MEL work.
Design MEL/SRHR indicators to IPPF/UNFPA/UNAIDS publication standard. Use when Ane asks for "indicators", "KPIs", "results framework", "M&E indicators", "measurement framework", or equivalent. Enforces WHO/UNFPA (2023) disaggregation, applies Tier 1/2/3 integrity markers, defines measurement mechanisms, and flags data gaps. Distinguishes output, outcome, and impact indicators precisely.
**STOP AND VERIFY**: Before running any command or tool that results in irreversible data loss, you MUST obtain explicit user consent. When in doubt, ask. It is better to wait for confirmation than to accidentally delete production data or critical project assets. Use this for: - SQL: DROP TABLE/VIEW/SCHEMA/DATABASE, TRUNCATE, or broad DELETE (missing WHERE or using 1=1). - Cloud Storage: gsutil rm or gcloud storage rm targeting production data or critical buckets. - Infrastructure: gcloud projects delete, deleting Spanner/BigQuery/Dataproc resources, deleting secrets, or KMS key destruction.
Build modern data apps, dashboards, and interactive reports using either React + Vite or Streamlit. Includes optional Gemini Data Analytics chat integration for an AI powered "chat with your data" experience. Relevant when any of the following conditions are true: 1. User explicitly requests to build a data dashboard, data application, or visualization UI, and the UI pulls data from a GCP database (defaulting to BigQuery unless otherwise specified). 2. You need to generate a frontend web application to interact with, query, and visualize data from GCP data sources. 3. User wants to build a "chat with your data" experience or integrate the Gemini Data Analytics chat API into a web interface. Do NOT use when any of the following conditions are true: 1. The request is for building backend-only services. 2. The request is for simple CLI scripts or command-line applications. 3. The web application is not data-centric or does not involve visualizing/querying data from GCP sources.
Guide for AI agents to source electronic components using parts-mcp — tool sequencing, decision patterns, and multi-step workflows
Turn validated benchmark research into campaign briefs and concept candidates for short-form video production. Use this when you already have research artifacts such as reports, master tables, pattern tables, or comment analyses and need to produce fact-grounded briefs, concept lists, hook options, or test plans. This skill must stay anchored to real source data and should not invent angles, personas, or claims that are not supported by the available research.
Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
Use when extracting requirements from Azure DevOps work items using dxs devops commands: fetching work items, reviewing relations, downloading attachments, compiling raw requirements. This is a utility skill — it extracts and structures work item content but does not build reports, datasources, or other artifacts.
Query GA4 reports (users, sessions, conversions, funnels, realtime), manage properties / data streams / key events / custom dimensions / audiences / access bindings, and send Measurement Protocol events via the `ga4` CLI. Use this skill whenever the user mentions GA4, Google Analytics, property IDs starting with `properties/`, tracking events, engagement or traffic metrics, attribution, conversions, key events, audiences, BigQuery links, access roles, or realtime users — even if they don't explicitly say "GA4". Do not use for Google Search Console (see google-search-console skill) or generic web analytics where the source isn't GA4 (ask first).
Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.
When the user wants to build a free tool for marketing — lead generation, SEO value, or brand awareness. Use when they mention 'engineering as marketing,' 'free tool,' 'calculator,' 'generator,' 'checker,' 'grader,' 'marketing tool,' 'lead gen tool,' 'build something for traffic,' 'interactive tool,' or 'free resource.' Covers idea evaluation, tool design, and launch strategy. For pure SEO content strategy (no tool), use seo-audit or content-strategy instead.