Ai skills

This skill runs the full code-change verification stack to ensure formatting, linting, typing, and tests pass after code changes.

This skill automates releasing all screenpipe monorepo components, bumps versions, generates changelogs, and triggers CI workflows to streamline shipping.

This skill lets you search your locally recorded screen, audio, and UI events to quickly recall meetings, apps used, and moments.

This skill helps designers and developers apply Screenpipe brand guidelines to UI, copy, and visuals while preserving privacy and consistency.

This skill performs discounted cash flow valuation to estimate intrinsic value per share and assess fair value against current price.

This skill initializes and optimizes multi-agent swarms by enforcing memory coordination, selecting topology, and configuring resources for reliable

This skill orchestrates a multi-agent code review swarm to identify security, performance, and architectural issues across PRs.

This skill helps orchestrate complex tasks by decomposing objectives, mapping dependencies, allocating resources, and estimating timelines for actionable plans.

This skill guides users to create new AI agent skills following the Agent Skills spec, adding instructions and patterns.

This skill models agent beliefs, desires, and intentions from RDF context, enabling explainable BDI reasoning and coherent multi-agent coordination.

This skill enables automated LLM-based evaluation pipelines, compares model outputs, and mitigates biases to deliver consistent, objective quality assessments.

This skill enables building and validating author-style fine-tuning pipelines from ePub to LoRA-trainable models for book voices.

This skill helps you design and implement multi-agent systems with context isolation, coordination patterns, and scalable architectures.

This skill helps manage and compress long agent conversations by optimizing tokens-per-task through anchored summaries and structured artifact tracking.

This skill helps you understand and design efficient context windows for AI agents, optimizing loading and budgeting across systems.

This skill helps you design and run multi-dimensional evaluation for agent systems, enabling robust benchmarking, continuous improvement, and quality gates.

This skill helps you design, optimize, and debug production agent systems through context engineering best practices and multi-agent architectures.

This skill helps you design and evaluate LLM-backed projects, selecting architecture, tasks, and cost estimates for efficient agent development.

This skill helps ensure thorough validation, error handling, and transparent reasoning across multi-source research tasks.

This skill helps you rapidly craft and publish compelling X job posts with visuals and automation.

This skill helps you design agent-native systems where agents are first-class, enabling atomic tools, loop execution, and open-ended capability.