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Claude Skills by fabioc-aloha
github.com/fabioc-aloha384 skills2 installs568 views
- Staleness DisciplineDetect, classify, and prune stale entries in Alex_Skill_Mall — define what stale means and how to remove gracefullyVotes: 0GitHub stars: 4
- Store AdoptionFetch plugin store updates, inventory contents, match against fleet profile, and generate adoption candidates reportVotes: 0GitHub stars: 4
- Store EvaluationEvaluate a proposed store for inclusion in Alex_Skill_Mall using a quality scorecardVotes: 0GitHub stars: 4
- Subagent OrchestratorCoordinate quota-aware parallel subagents for large, multi-file Antigravity tasks.Votes: 0GitHub stars: 4
- Version ManagementSemver discipline for Alex_ACT_Edition — bump rules, breaking-change classification, fleet rollout sequencingVotes: 0GitHub stars: 4
- Chart Big IdeaDistill 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...Votes: 0GitHub stars: 4
- Flint ChartUse 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.Votes: 0GitHub stars: 4
- Render VerifyVerify 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...Votes: 0GitHub stars: 4
- Md To PdfConvert Markdown to PDF via Pandoc with two rendering engines.Votes: 0GitHub stars: 4
- Data PreparationData cleaning, profiling, transformation, and quality gates -- prepares raw data for visualization and analysisVotes: 0GitHub stars: 4
- Datasource ConnectorsIngestion patterns for CSV, JSON, REST API, SQL, Excel, and Parquet -- guides an LLM through loading data from any common sourceVotes: 0GitHub stars: 4
- Delivery Ascii DashboardRender 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.Votes: 0GitHub stars: 4
- Delivery Html DashboardRender 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.Votes: 0GitHub stars: 4
- Delivery Svg MarkdownRender 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.Votes: 0GitHub stars: 4
- Storytelling RequirementsGuided requirements template for data storytelling projects -- walks users through audience, Big Idea, questions, data sources, and delivery target before any chart is createdVotes: 0GitHub stars: 4
- Visual StorytellingBundle plugin: installs the complete Visual Storytelling pipeline (brief, ingest, clean, select, deliver). See component SKILLs for detailed specs.Votes: 0GitHub stars: 4
- Visual VocabularyChart catalog organized by communication goal, CSAR evaluation loop for AI-generated charts, 5-visual rule, override decision framework, and living gallery referencesVotes: 0GitHub stars: 4
- Md To PdfConvert Markdown to PDF via Pandoc with two rendering engines.Votes: 0GitHub stars: 4
- Data PreparationData cleaning, profiling, transformation, and quality gates -- prepares raw data for visualization and analysisVotes: 0GitHub stars: 4
- Datasource ConnectorsIngestion patterns for CSV, JSON, REST API, SQL, Excel, and Parquet -- guides an LLM through loading data from any common sourceVotes: 0GitHub stars: 4
- Delivery Ascii DashboardRender 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.Votes: 0GitHub stars: 4
- Delivery Html DashboardRender 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.Votes: 0GitHub stars: 4
- Delivery Svg MarkdownRender 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.Votes: 0GitHub stars: 4
- Storytelling RequirementsGuided requirements template for data storytelling projects -- walks users through audience, Big Idea, questions, data sources, and delivery target before any chart is createdVotes: 0GitHub stars: 4
- Visual VocabularyChart catalog organized by communication goal, CSAR evaluation loop for AI-generated charts, 5-visual rule, override decision framework, and living gallery referencesVotes: 0GitHub stars: 4
- Visual StorytellingBundle plugin: installs the complete Visual Storytelling pipeline (brief, ingest, clean, select, deliver). See component SKILLs for detailed specs.Votes: 0GitHub stars: 4
- Mcp Client IntegrationSafely consume an MCP server someone else wrote — evaluate it before installing, register it correctly, scope its credentials, and diagnose it when it misbehaves.Votes: 0GitHub stars: 4
- Mcp Server BuildImplement an MCP server in TypeScript, Python, or C#/.NET, and register it with a host. Working stdio and HTTP samples verified against the published SDKs.Votes: 0GitHub stars: 4
- Mcp Server DesignDecide whether to build an MCP server, which protocol primitives to expose, and how to design tools an agent can actually use. Covers transports, language choice, and the tools/resources/prompts split.Votes: 0GitHub stars: 4
- Mcp Server HardeningSecure an MCP server that is reachable over a network — host-name validation against DNS rebinding, CORS restraint, authentication, secret handling, and the confused-deputy problem.Votes: 0GitHub stars: 4
- Mcp Server OperationsShip, version, and run an MCP server after it works — packaging and distribution, breaking-change discipline, deployment shapes, and debugging failures that only appear under a host.Votes: 0GitHub stars: 4
- Mcp Server TestingProve an MCP server works and that an agent can actually use it. Covers the Inspector, a ten-question evaluation set, and the difference between responding correctly and being usable.Votes: 0GitHub stars: 4
- Assess BrainAssess active Markdown brain files in a local AI agent project or plugin source without changing it. Use before modifying a brain or reviewing declared instructions, skills, prompts, agents, bundled Markdown resources, and research documentation.Votes: 0GitHub stars: 4
- Compile BrainCreate or improve a Markdown instruction, skill, prompt, or agent from an explicitly selected file or user-identified text. Use when a user asks to optimize an existing brain artifact or create one for consistent future execution.Votes: 0GitHub stars: 4