Claude Skills by fabioc-aloha

Detect, classify, and prune stale entries in Alex_Skill_Mall — define what stale means and how to remove gracefully

Fetch plugin store updates, inventory contents, match against fleet profile, and generate adoption candidates report

Evaluate a proposed store for inclusion in Alex_Skill_Mall using a quality scorecard

Coordinate quota-aware parallel subagents for large, multi-file Antigravity tasks.

Semver discipline for Alex_ACT_Edition — bump rules, breaking-change classification, fleet rollout sequencing

Distill the one-sentence Big Idea, story arc, audience, and style stance for a chart BEFORE picking a chart type. Starts by questioning intent — whether the artifact should exist at all, and whether the stated purpose is the real one. Reads the surrounding docs / prose / ticket for an existing Big Idea first, then helps the user articulate one via a 3-question elicitation ladder if none is found. Asks whether the user wants a TRADITIONAL (safe) or INNOVATIVE (higher-impact, higher-risk) treat...

Use when the user wants to visualize data — from 'which chart should I use?' to 'render this'. Helps pick the right chart from the analytical question (comparison / trend / distribution / relationship / proportion / flow / KPI), then authors a ChartAssemblyInput and renders via the flint-chart-mcp server (Vega-Lite / ECharts / Chart.js). Transform data before Flint; style tweaks after Flint.

Verify a rendered visual artifact actually says what it was supposed to say — open it, read its console errors, walk a failure catalog, and check it against the claim it was meant to carry. Works on charts, generated HTML reports, SVG, dashboards, diagrams, and any other output meant to be looked at. Use after render_chart / create_chart_view, after editing a post-Flint Vega-Lite spec, and before committing any generated HTML/SVG/PNG. Satisfied by the host's built-in browser tools or by the o...

Convert Markdown to PDF via Pandoc with two rendering engines.

Use when adding interactive 3D scenes from Spline.design to web projects, including React embedding and runtime control API.

Data cleaning, profiling, transformation, and quality gates -- prepares raw data for visualization and analysis

Ingestion patterns for CSV, JSON, REST API, SQL, Excel, and Parquet -- guides an LLM through loading data from any common source

Render data dashboards as pure ASCII art in monospace text -- the cheapest, most portable delivery method. No rendering engine, no SVG, no browser. LLM-native output with predictable character geometry.

Render data dashboards as self-contained HTML files using Apache ECharts v6. Single file, zero build step, interactive charts with tooltips and data zoom. Declarative JSON option config optimized for AI generation.

Render data dashboards as static SVG panels embeddable in Markdown. Uses D3.js v7 mental model for scales, shapes, and axes. No runtime JS; output is pure SVG with inline styles for GitHub compatibility.

Guided requirements template for data storytelling projects -- walks users through audience, Big Idea, questions, data sources, and delivery target before any chart is created

Bundle plugin: installs the complete Visual Storytelling pipeline (brief, ingest, clean, select, deliver). See component SKILLs for detailed specs.

Chart catalog organized by communication goal, CSAR evaluation loop for AI-generated charts, 5-visual rule, override decision framework, and living gallery references

Distill the one-sentence Big Idea, story arc, audience, and style stance for a chart BEFORE picking a chart type. Starts by questioning intent — whether the artifact should exist at all, and whether the stated purpose is the real one. Reads the surrounding docs / prose / ticket for an existing Big Idea first, then helps the user articulate one via a 3-question elicitation ladder if none is found. Asks whether the user wants a TRADITIONAL (safe) or INNOVATIVE (higher-impact, higher-risk) treat...

Use when the user wants to visualize data — from 'which chart should I use?' to 'render this'. Helps pick the right chart from the analytical question (comparison / trend / distribution / relationship / proportion / flow / KPI), then authors a ChartAssemblyInput and renders via the flint-chart-mcp server (Vega-Lite / ECharts / Chart.js). Transform data before Flint; style tweaks after Flint.

Verify a rendered visual artifact actually says what it was supposed to say — open it, read its console errors, walk a failure catalog, and check it against the claim it was meant to carry. Works on charts, generated HTML reports, SVG, dashboards, diagrams, and any other output meant to be looked at. Use after render_chart / create_chart_view, after editing a post-Flint Vega-Lite spec, and before committing any generated HTML/SVG/PNG. Satisfied by the host's built-in browser tools or by the o...

Convert Markdown to PDF via Pandoc with two rendering engines.

Data cleaning, profiling, transformation, and quality gates -- prepares raw data for visualization and analysis

Ingestion patterns for CSV, JSON, REST API, SQL, Excel, and Parquet -- guides an LLM through loading data from any common source

Render data dashboards as pure ASCII art in monospace text -- the cheapest, most portable delivery method. No rendering engine, no SVG, no browser. LLM-native output with predictable character geometry.

Render data dashboards as self-contained HTML files using Apache ECharts v6. Single file, zero build step, interactive charts with tooltips and data zoom. Declarative JSON option config optimized for AI generation.

Render data dashboards as static SVG panels embeddable in Markdown. Uses D3.js v7 mental model for scales, shapes, and axes. No runtime JS; output is pure SVG with inline styles for GitHub compatibility.

Guided requirements template for data storytelling projects -- walks users through audience, Big Idea, questions, data sources, and delivery target before any chart is created

Chart catalog organized by communication goal, CSAR evaluation loop for AI-generated charts, 5-visual rule, override decision framework, and living gallery references

Bundle plugin: installs the complete Visual Storytelling pipeline (brief, ingest, clean, select, deliver). See component SKILLs for detailed specs.