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Advanced PDF Analysis and Synthesis

meta-pdf-intelligence

opensquilla/opensquilla

This meta-skill orchestrates a comprehensive workflow for analyzing PDF documents. It handles complex tasks such as summarizing, cross-document comparison, and targeted Q&A. It ensures findings are traceable by indexing evidence from various sources (full PDFs, pasted excerpts, etc.) and synthesizing structured insights across multiple files.

Pre-Commit Code Quality Gate

meta-pre-commit-quality-gate

opensquilla/opensquilla

This meta-skill runs three essential quality gates (ruff, mypy, and pytest) concurrently against the staged changes. It provides a comprehensive, CI-like check locally, offering a single BLOCK or APPROVE verdict to ensure code readiness before committing. It combines static analysis, type checking, and unit testing into one workflow.

Research To Slide Deck Generator

meta-research-to-slide-deck

opensquilla/opensquilla

This meta-skill orchestrates a multi-step process to transform complex research questions, data, or deep reports into a structured, source-backed presentation deck (PPTX). It automatically handles searching, source curation, synthesizing an executive storyline, and generating a professional slide outline and talk track, making it ideal for competitive analysis, leadership briefings, or academic presentations.

Combinator Security Review Bundle

meta-security-review-bundle

opensquilla/opensquilla

This meta-skill implements a combinator pattern for deep security analysis. It runs three independent gates—policy governance, secret scanning, and audit logging—over a candidate operation. It enforces a strict arbitration rule (Policy DENY > Scanner WARN > ALLOW) to provide a robust, multi-layered verdict, making it ideal for reviewing critical code changes or environment modifications for safety compliance.

Workbook Insight Analysis Pipeline

meta-spreadsheet-insight

opensquilla/opensquilla

This meta-skill automates the entire process of transforming raw Excel data into structured business insights. It reads the raw data, performs advanced trend and anomaly analysis, writes the resulting findings to a dedicated 'Insights' sheet, and persists key performance indicators (KPIs) to long-term memory. Ideal for comprehensive business reviews and data-driven decision-making.

Stack Trace Error Investigator

meta-stack-trace-investigator

opensquilla/opensquilla

This meta-skill is designed to automate the diagnosis of complex programming errors. When presented with a stack trace, traceback, or failing log, it orchestrates a multi-step investigation. It parses the trace, searches the repository history, checks relevant issues, and analyzes code diffs to provide a comprehensive brief for root cause analysis and debugging.

Generic Stack Trace Analysis Probe

stack-trace-generic-probe

opensquilla/opensquilla

An internal, language-agnostic probe designed for investigating complex stack traces when the source language is unknown. It analyzes the provided trace to output structured, language-neutral elements, including failure contract checks, minimal reproduction guidance, and specific patch targets. This tool is vital for robust failure analysis and debugging across diverse codebases.

Go Stack Trace Debugging Probe

stack-trace-go-probe

opensquilla/opensquilla

An internal diagnostic tool designed for analyzing Go language panics and complex stack traces. It provides structured guidance, including Go-specific nil/error checks, minimal reproducible `go test` commands, and precise patch targets, enabling highly efficient root cause analysis and debugging for Go projects.

Semantic Model Downstream Lineage Analysis

lineage-analysis

data-goblin/power-bi-agentic-development

This tool traces the entire downstream dependency chain from a core semantic model to all connected reports and assets across multiple Fabric workspaces. Use it for crucial impact analysis before modifications, auditing model usage, or mapping cross-workspace data dependencies. It helps data stakeholders understand the full scope of influence a model has on the reporting layer.

Python Visuals for Power BI Reports

data-goblin/power-bi-agentic-development

A comprehensive guide and set of tools for embedding dynamic Python visualizations (using matplotlib and seaborn) into Power BI reports. It details the structured workflow, including script injection, data handling (dataset DataFrame), and mandatory best practices for generating static PNG output. Ideal for advanced data analysis and complex reporting.

Semantic Model Lifecycle and Governance

data-goblin/power-bi-agentic-development

A comprehensive guide for managing the entire lifecycle of tabular data models (Semantic Models) in Power BI/Analysis Services. It provides best practices and a tool cascade (CLI, TOM, TMDL) for designing, building, optimizing, refreshing, and auditing models. Use this skill when performing advanced model operations, optimizing performance, or ensuring data quality.

Calculate Statistical Power And Sample Size

statistical-power

K-Dense-AI/scientific-agent-skills

Calculates statistical power and required sample sizes for study planning. It supports both closed-form methods (for standard tests like t-tests, ANOVA) and simulation-based methods (for complex models like mixed models or survival analysis). Use this skill to determine the minimum detectable effect (MDE) or justify sample sizes for grants and IRB protocols before data collection.

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