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Search team activity in Screenpipe Enterprise and review records by device and time. Preview, deploy, and schedule managed Pipes, which are AI automations, with explicit targets and checks before changes.
Operate Screenpipe from the terminal to set up continuous recording, check capture health, and search local history. Manage Pipes, scheduled AI automations, and configure and test connections to external services.
Create and manage scheduled AI automations in screenpipe from the command line. Enable or disable jobs, test runs, inspect logs, and configure service connections such as Telegram and Slack, including connection status checks.
Automate Apipie AI tasks through Rube MCP, a connection for agent tools. The skill discovers available operations, checks the service connection, and uses current input requirements to carry out supported workflows.
Automate Apipie AI tasks through Rube MCP, a connection for agent tools. The skill discovers available operations, checks the service connection, and uses current input requirements to carry out supported workflows.
Find past discussions across existing screenpipe, Codex, Claude, Cursor, and Gemini CLI chats by title, workspace, or message text. With explicit authorization, send follow-up work to a specific supported chat; Gemini CLI supports search only.
Create charts, dashboards, scorecards, and styled summaries as standalone HTML reports for the screenpipe viewer. Keep styles, scripts, and images inside the file so the report renders in a sandbox with no network access.
Check Screenpipe's process, API, screen capture, and audio transcription status. Inspect logs, storage, resource usage, and processing metrics to identify problems, then report the findings with relevant errors and suggested fixes.
Use Screenpipe’s local REST API, an interface for programmatic requests, to search screen and meeting history, review app activity and active time, retrieve synced-device records, export recordings, and rerun audio transcription.
Find past decisions, documents, and conversations in Screenpipe recordings. Get an answer with timestamps and available source links, with clear distinctions between recorded evidence, inference, and gaps in coverage.
[omh] CRM pipeline or sales forecast to review: turn a supplied CRM export or pipeline snapshot into an evidence-bound pipeline health, forecast, and follow-up review. Aliases: pipeline-review, forecast-review, deal-review. Use when the user says: sales-pipeline-review, sales pipeline review, pipeline review, pipeline health, pipeline coverage, deal review, deal health, sales forecast review.
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Sets up a Power Platform Pipeline for automated Power Pages deployments. Power Platform Pipelines is Microsoft's native CI/CD tool built into the Power Platform — no external infrastructure required. Use when asked to: "set up ci/cd", "create pipeline", "setup pipeline", "set up power platform pipelines", "create power pipelines", "automate deployments", "set up automated deployment", "create deployment pipeline", "use power pipelines". Also handles: "set up github actions" or "set up azure devops pipeline" (shows coming-soon guidance for those platforms).
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Ensures the tenant has a usable Power Platform Pipelines host environment before any pipeline operation runs. Detects host state via the same resolution order as the Power Apps UI (org-db setting → BAP env metadata → default-custom-host setting); if any existing host (Platform or Custom) is found, uses it. If no host is bound to the source env, provisions a new **Platform Host** (recommended, idempotent) or a **Custom Host** via the BAP env-create API with the `D365_ProjectHost` template, or guides the user through PPAC install / `New custom host` (manual fallbacks). Polls lifecycle operations, verifies the host responds to Pipelines API calls, writes a host-check artifact other ALM skills consume. Use when asked to: "set up pipelines host", "ensure pipelines host", "no pipelines host", "install pipelines", "create pipelines host", "provision platform host", "provision custom host". Also invoked transparently by /power-pages:setup-pipeline when its host discovery step finds nothing.
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Configuring and running Pipeline Inspection in Sales Cloud: enabling the feature, mapping forecast categories into the inspection view, Days in Stage and other deal-change metrics, and pipeline review cadence for sales managers. Use when designing or improving how a team monitors deal health and pipeline movement. NOT for the Revenue Intelligence app, Einstein deal insights, or forecast-accuracy dashboards — use admin/revenue-intelligence-setup. NOT for forecast types, quotas, or forecast hierarchy setup — use admin/collaborative-forecasts. Keywords: pipeline review, coverage ratio, stage conversion, slippage, stale deals, days in stage, LastStageChangeInDays, LastStageChangeDate, AgeInDays, PushCount, ForecastCategoryName, enablePipelineInspection, PipelineInspMetricConfig, OpportunitySettings, review cadence, commit call.
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Structured 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for individual project folders within a pipeline, e.g. a single software tool or paper project). Triggers on tasks like "improve pipeline X", "optimize the stack", "rebuild Y", "renovation", "pipeline refactoring", "clean up project folder", "improve folder structure", "unify conventions", "documentation consolidation", "integrate into existing system", or any substantial intervention in established structures. Delivers building-stock analysis, purpose clarification, ideal sketch, gap plan, empirical pain-point identification, and retests with fresh subagents. Prevents parallel standards, duplication, and pipeline breaks.
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Build custom cognee processing by chaining Python tasks, defining data types, and saving results to graph and vector databases. Use it to enrich existing data, inspect run status, and troubleshoot how tasks pass data.
Turn selected Screenpipe activity into a concise recap for a defined audience. Summarize outcomes from recorded evidence, then review the draft to remove identifying details, private links, sensitive amounts, and unnecessary personal information before sharing.
Retrieve and analyze Screenpipe recording engine and desktop app logs to investigate errors or events at a specific time. Get timestamped findings, recurring error patterns, possible causes, suggested fixes, and indications of service status.
Develop and test Windows-specific Screenpipe changes on a disposable Azure virtual machine. The workflow verifies native behavior, preserves logs and desktop video, and handles branch and pull request delivery when authorized.
Investigate and maintain documented workflows using Screenpipe evidence and shared drafts. Review whether recorded actions support each procedure, preserve verified steps, and add timing measurements only when clear start and end evidence is available.
Review and improve code changes on the current branch using Pipecat conventions. Refine names and structure, add type hints and documentation, check example patterns, and make conservative performance improvements while preserving compatibility.
Research new models and API capabilities offered by providers behind Pipecat services. Produce dated reports for each service and local committed branches for clear updates, with review commands and separate publishing steps.
Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.
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Procedimiento estructurado de 6 pasos para mejorar, renovar o reconstruir pipelines existentes, carpetas de proyectos individuales, estructuras de documentación o stacks de software. Direccionable como "pipeline optimizer" (para pipelines temáticos completos, p. ej. de software, investigación o desarrollo de videojuegos) o "project-folder optimizer" (para carpetas de proyectos individuales dentro de un pipeline, p. ej. una herramienta de software o proyecto de artículo académico). Se activa ante tareas como "mejorar pipeline X", "optimizar el stack", "reconstruir Y", "renovación", "refactorización de pipeline", "limpiar carpeta de proyecto", "mejorar estructura de carpetas", "unificar convenciones", "consolidación de documentación", "integrar en sistema existente" o cualquier intervención sustancial en estructuras establecidas. Proporciona análisis del estado actual, aclaración del propósito, boceto del estado ideal, plan de brechas, identificación empírica de puntos de dolor y reevaluación con subagentes limpios. Previene estándares paralelos, duplicación y rupturas en el pipeline.
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