Skill UI

This advanced tool generates a comprehensive, five-section academic paper outline (Abstract, Introduction, Method, Results, Discussion). Given a research topic, preferred style, and curated reference sources, it crafts a detailed narrative backbone aiming for 6,500-8,000 words. It ensures that each section contains sufficient concrete substance, sub-topics, and specific findings, providing a robust foundation for authors to expand into a full, high-quality research manuscript.

Use the Composio CLI to automate the entire Pull Request review and Continuous Integration (CI) triage process for GitHub and GitLab. This tool fetches code diffs, analyzes failure logs, posts detailed inline review comments, and iteratively patches and re-runs CI checks until the code passes, significantly enhancing code quality and developer efficiency.

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. This tool accepts structured English prompts, an optional first-frame image, and an optional identity/style reference image for continuity. It supports dual backends (OpenRouter, Volcengine, BytePlus) to maximize accessibility and reliability for cinematic shot generation.

This system creates and registers high-quality, reusable synthetic voices (voice clones) from local audio samples. It operates under a strict, consent-first workflow, requiring explicit speaker consent, detailed use permissions, and source verification before cloning. It is designed for professional Text-to-Speech (TTS) applications, IVR systems, or training content development where a consistent, branded voice is essential.

This skill provides a comprehensive framework for evaluating Power BI reports. It assesses report quality, usage adoption rates, performance metrics, and structural integrity across different lifecycle stages (development, testing, active use). It analyzes usage data, audience reach, and performance bottlenecks, generating actionable feedback and optimization recommendations to ensure reports are effective and maintainable.

This skill provides a deterministic, git-only method to verify claims made by AI agents (e.g., 'done', 'shipped', 'fixed'). Instead of trusting the agent's self-report, it audits the commit's diff and git history using the DOS kernel (`dos verify`, `dos commit-audit`) to confirm if the claimed change genuinely occurred and is backed by non-forgeable evidence. It acts as a critical quality gate.

A crucial post-hoc review skill designed for AI-generated Markdown prose. It audits content against a comprehensive set of 21 stylistic and structural rules using both deterministic mechanical checks and deep semantic judgment. Users can audit a single file to get a detailed scorecard, or compare two drafts (A/B) for regression testing. Furthermore, it can optionally generate a polished, revised copy in a separate file, ensuring the integrity of the original document while significantly improving linguistic quality and adherence to style guides. Ideal for refining AI-written documentation, ...

A specialized quality gate skill designed to review complex, multi-source outputs generated by the CrossFrame framework. It rigorously checks reasoning fidelity, evidence boundaries, source anchors, and structural continuity. Use this when advanced verification of logical rigor and source integrity is required, ensuring outputs meet strict internal protocols and avoid common structural failures.

A sophisticated automated loop that uses vision or video models to evaluate subjective aesthetic quality (e.g., timing, color grade, layout). Instead of relying on numeric metrics, the system renders multiple parameterized variants into one artifact, asks the AI to rate them, and suggests optimal values, repeating the process until convergence. Ideal for design iteration where human judgment is the primary success criteria.

A comprehensive playbook for optimizing the entire lifecycle of pull requests. It guides developers through systematic pre-flight cleanup, critical self-audits, local test verification, and structuring high-signal PR descriptions to ensure code quality and fast maintainer approval.

This comprehensive guide details the idiomatic and efficient way to write Scala code. It covers crucial modern practices, such as utilizing functional transforms over traditional loops, embracing pattern matching, using Option/Either for robust error handling instead of null checks or exceptions, and managing concurrency safely. Essential reading for any Scala developer aiming for high-quality, maintainable, and performant codebases.

Implements a robust, four-stage coding discipline (Plan, Isolate, Test First, Double Review) to prevent premature code delivery. This skill forces the AI to structure complex tasks by planning, implementing in isolation, writing tests first, and performing deep self-review, significantly improving code correctness and quality.