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data ai productivity tools AI Skills

Discover data ai productivity tools skills, compare source repositories and read the instructions for each workflow.

Categories: data ai productivity tools

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GitHub

customer-support-builder

nbashaw

Guide users through building a custom customer support automation skill for their company. Walks through planning integrations, writing scripts for their support stack (Zendesk, HelpScout, Intercom, etc.), crea...

GitHub

skild

Peiiii

Skill package manager for AI Agents — install, manage, and publish Agent Skills.

GitHub

doc-splitter

jmagly

Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN. Use when relevant to the task.

GitHub

pr-reviewer

jmagly

Review GitHub pull requests for code quality, security, and best practices. Use for automated PR feedback and approval workflows.

GitHub

skill-enhancer

jmagly

AI-powered enhancement of skill SKILL.md files. Use to transform basic templates into comprehensive, high-quality skill documentation.

GitHub

decision-support

jmagly

Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis. Use when relevant to the task.

GitHub

sdlc-reports

jmagly

Generate comprehensive SDLC reports including iteration status, metrics dashboards, and executive summaries. Use when relevant to the task.

GitHub

artifact-orchestration

jmagly

Orchestrate multi-agent artifact generation with the Primary Author → Parallel Reviewers → Synthesizer → Archive pattern. Use when relevant to the task.

GitHub

approval-workflow

jmagly

Multi-stakeholder approval routing with status tracking and escalation. Use when relevant to the task.

GitHub

audience-synthesis

jmagly

Synthesize audience insights from multiple data sources into unified personas and segments. Use when relevant to the task.

GitHub

data-pipeline

jmagly

Orchestrate marketing data collection, transformation, and reporting workflows. Use when relevant to the task.

GitHub

skill-builder

jmagly

Build Claude skills from extracted documentation. Use after doc-scraper/pdf-extractor to generate uploadable skill packages. Use when relevant to the task.

GitHub

skill-builder

jmagly

Build Claude skills from extracted documentation. Use after doc-scraper/pdf-extractor to generate uploadable skill packages.

GitHub

skill-enhancer

jmagly

AI-powered enhancement of skill SKILL.md files. Use to transform basic templates into comprehensive, high-quality skill documentation. Use when relevant to the task.

GitHub

architecture-evolution

jmagly

Manage architecture changes with impact analysis, ADR generation, and migration planning. Use when relevant to the task.

GitHub

performance-digest

jmagly

Generate executive-ready performance summaries with insights and recommendations. Use when relevant to the task.

GitHub

skill-packager

jmagly

Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package. Use when relevant to the task.

GitHub

test-coverage

jmagly

Analyze test coverage, identify gaps, and recommend test improvements. Use when relevant to the task.

GitHub

nl-router

jmagly

Route natural language requests to appropriate skills and workflows. Use when relevant to the task.

GitHub

doc-splitter

jmagly

Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN.

GitHub

sanity-groq

sanity-io

Expert assistance for writing, optimizing, and debugging GROQ queries. Use when writing queries or debugging performance.

GitHub

bd-issue-tracking

open-constructs

Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles....

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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