Skill UI

Automates iterative use of the plugin-dev skill-reviewer agent to diagnose and fix Claude Code SKILL.md issues, driving repeated review/fix cycles until standards are met before emitting the completion marker.

Guides an agent to critically review a written implementation plan, execute every outlined step with required verifications, and hand off completion via finishing-a-development-branch procedures, ensuring blockers prompt clarification.

Guides branch completion by verifying tests, identifying the base branch, presenting merge/PR/keep/discard options, and cleaning up worktrees when appropriate.

Framework ensuring no completion claims are made until fresh verification commands are run and their outputs read, so tests/builds/regressions are proven before anyone says the work is done.

This comprehensive guide outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

Guides experts through auditing and experimenting on non-registration forms to boost completion rates, covering assessment, design, copy, layout, and hypothesis testing for lead, contact, demo, survey, or checkout flows.

Guides CRO experts through diagnosing signup friction, evaluating form fields and steps, and recommending quick wins, high-impact changes, and experiments to lift completion rates across trials, freemium, paid, and waitlist flows.

This skill provides sophisticated project estimation by adapting to human-only, hybrid, or agent-first development modes. It uses research-backed PERT statistics and confidence bands (P50, P75, P90) to forecast development timelines for tasks, backlogs, and capacity planning. It continuously calibrates estimates based on actual completion data, ensuring accuracy in AI-assisted and hybrid development environments.

Tubeify automates YouTube video editing via API: it trims pauses, removes filler words, and polls for completion so creators upload polished recordings without manual editing.

PIP kicks in when tasks fail repeatedly or the assistant becomes passive, layering Western big-tech performance rhetoric, a systematic debugging methodology, and proactivity enforcement so every code, ops, research, deployment, or writing task is owned, verified, and driven to completion.

Automates the complete DocuSign e-signature lifecycle using Rube MCP. This tool enables users to list document templates, create and send secure envelopes, assign recipient roles, and monitor real-time signing status. It streamlines document management and contract workflows from draft to completion.