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Blog Post

OrganizationPopular
nteract
blog-post

Author a new entry for the Semiotic blog. Use this skill whenever the user asks for a blog post, release summary, chart explainer, or case study to publish at /blog/SLUG.

Overview

Publishernteract
Repositorysemiotic
Skill nameblog-post
Stars
2.7K
Forks
142
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nteract on GitHub. Read the source before you install it.

Installation

Install the Blog Post AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nteract/semiotic/tree/main/.agents/skills/blog-post
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nteract/semiotic.git /tmp/semiotic
mkdir -p .claude/skills
cp -r /tmp/semiotic/.agents/skills/blog-post .claude/skills/blog-post
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Post in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blog Post on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blog Post is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Writing a Semiotic blog post

This skill writes one entry for the Semiotic blog. The blog lives at /blog/; entries live at /blog/<slug>/. Three story shapes are supported — pick the one that matches what's being written:

  1. Chart explainer — single chart, "what / why / when / wiring".
  2. Release summary — what's new in a version, ordered by impact.
  3. Narrative / case study — comparative posts ("X vs Y"), walkthroughs, recreations of historical visualizations.

Every entry follows the same structure regardless of shape. The why-care section is non-negotiable: the post has to give the reader a reason to read it that lands even if they're not currently using Semiotic. The blog isn't reference docs; it's a publication that happens to be hosted on the docs site.

Before writing anything

Ask the user for the author byline unless they've already given one. Don't assume "Elijah Meeks" by default — many entries will be co-authored or attributed to "Semiotic Team" for releases. One short question, then proceed.

File structure

For a new entry with slug <slug>:

  1. Body component — docs/src/blog/entries/<slug>.jsx. Default export is { slug, title, subtitle, author, date, tags, excerpt, component, ogChart? }. The component is a React function returning JSX (the entry's body — no header, no chrome, the BlogEntryView wraps it).
  2. Register in registry — docs/src/blog/entries.js imports the new file and adds it to blogEntries.
  3. Register in metadata mirror — docs/src/blog/entries-meta.js gets the same metadata object (without component, without the React imports). This mirror is read by the OG-card generator and the prerender script, both of which run under plain Node and can't load JSX.

Both registry files must stay in sync. The OG-card generator and prerender script read entries-meta.js; the React app reads entries.js.

Required fields

js
{
  slug: "kebab-case-route",
  title: "Title-Case Headline",
  subtitle: "One or two sentences orienting the reader.",
  author: "Author Name",                  // ASK THE USER if unspecified
  date: "YYYY-MM-DD",                     // ISO; controls sort order
  tags: ["release"] | ["chart-explainer", "xy"] | ...,
  excerpt: "2–3 sentence preview shown on the index card.",
  component: Body,                        // function returning JSX
  ogChart: { component: "DifferenceChart" }, // optional, see OG step
}

Tags vocabulary

Pick freely from:

  • Shape: release, chart-explainer, case-study, tutorial
  • Family: xy, network, geo, ordinal, realtime, hierarchy

Multi-tag is fine and encouraged. Don't invent new top-level tags without checking the existing taxonomy in entries.js.

The skeleton — applies to all shapes

Every entry MUST have these sections (with the names below as h2 headings, except the intro):

  1. Opening paragraph (no heading) — one paragraph that orients the reader. State the chart / topic in concrete terms. Don't start with "In this post we will…". Start with the thing.
  2. Why this exists / why care — answer "why should I care about this if I'm not currently using Semiotic?". Even chart-explainer posts need this: tell the data-viz audience what makes the chart-type interesting, then connect it to Semiotic's implementation.
  3. The thing itself — live demo, or release-note bullets, or the comparative pair. This is the meat. Show, don't tell.
  4. How to read / how it works — once the reader has seen the thing, walk them through how to read the visual encoding (for chart posts) or where to look for the API change (for releases).
  5. When to reach for it / when not — guidance. Pair every "use it for X" with "don't use it for Y, use Z instead". This is the section that earns the reader's trust.
  6. Wiring it up — minimal code snippet showing the prop shape. For releases, link to the changelog and migration notes.
  7. Related — link to neighbor charts, related features, and the full reference page.

The Why and the When-to-reach sections are what distinguish a Semiotic blog post from the reference docs at /charts/<name>. The reference doc tells you what's there; the blog post tells you when you'd care.

Story-shape specifics

Chart explainer

  • Title format: <ChartName>, explained.
  • Opening: one-sentence elevator pitch. ("DifferenceChart is the chart you reach for when the story is the gap between two series, not either series on its own.")
  • Why-care section: cover the general data-viz problem the chart solves, NOT the Semiotic-specific API. The same audience that reads HN data-viz threads should find this useful. Then add a paragraph relating it to Semiotic's implementation (e.g. "in Semiotic this is wired through…").
  • Live demo: one self-contained chart with inline synthetic data. Keep the data small enough that the reader can imagine the underlying rows (5–15 rows is the sweet spot).
  • When-to-reach section: list 3–5 cases for it, then 3 cases against it pointing to the right alternative chart.
  • Wiring section: ≤15 lines of code. Just the minimum props.
  • Streaming / push mode section — REQUIRED for every chart explainer. Three pieces:
    1. A live push demo using BlogPushDemo from docs/src/blog/components/BlogPushDemo.jsx. Hand it a chartRef, the frames array (one entry per step), a pushAt(ref, row, i) callback that calls the chart's push method, and a resetAt(ref) callback that calls clear(). The demo gives the reader Play / Step / Reset controls and a step counter for free.
    2. A push-mode wiring snippet — ≤15 lines — showing the ref, the push() / update() calls relevant to the chart, and any required *IdAccessor (XY charts want pointIdAccessor; ordinal charts want dataIdAccessor; network HOCs use nodeIDAccessor / edgeIdAccessor).
    3. A "why push helps here" paragraph specific to this chart's nature. Generic boilerplate is worthless; the story has to land on a property the reader can map back to their own code. Examples from the seeded entries:
      • DifferenceChart: segment recomputation is cheap and in-buffer; setting data on every tick triggers React reconciliation that push skips.
      • QuadrantChart: update(id, fn) mutates one point without re-keying the rest; preserves hover and in-flight tooltips.
      • FunnelChart: bar-and-trapezoid size deltas are animated; data resets lose the animation. Charts that explicitly DO NOT support push (hierarchy HOCs: OrbitDiagram, TreeDiagram, Treemap, CirclePack) get a different streaming section that explains WHY push doesn't apply (the layout reads the full tree, not incremental appends) and the pattern that does work (set the data prop to a new tree; the chart's transitions still ease cleanly between trees).
  • Tags: ["chart-explainer", "<family>"].
Push-mode demo skeleton

Inside the entry file, alongside the static Body function, declare a PushDemo function that wires BlogPushDemo:

jsx
function PushDemo() {
  const chartRef = useRef(null)
  return (
    <div style={chartFrame}>
      <ThemeProvider theme="carbon-dark">
        <BlogPushDemo
          chartRef={chartRef}
          frames={DEMO_DATA}                 // array, one item per step
          pushAt={(ref, row) => ref?.push?.(row)}
          resetAt={(ref) => ref?.clear?.()}
        >
          <YourChart
            ref={chartRef}
            // ...the same props as the static demo, MINUS `data`
            pointIdAccessor="id"             // or dataIdAccessor etc.
          />
        </BlogPushDemo>
      </ThemeProvider>
    </div>
  )
}

Then reference <PushDemo /> from inside <Body>'s streaming section. Keep the same chart frame styling as the static demo so the visual continuity between the two reads as "same chart, two flavors."

Release summary

  • Title format: Semiotic <X.Y.Z> (no "released today" or other date-stamped language; the entry's own date carries that).
  • Opening: one sentence summarizing the release's theme ("3.5.2 is mostly a factor-and-extend release."). Link to the full CHANGELOG entry on GitHub.
  • Why-care section: optional for releases, but if there's a big-picture story (new hook family, new chart, architecture shift) tell it here.
  • Sections: one h2 per major feature group, ordered by impact. Use the actual feature names so the reader can grep CHANGELOG.
  • Upgrade notes h2: any breakages or behavior changes, even small ones. Be explicit about what to do if affected.
  • No live demos required; link to the docs pages for new features.
  • Tags: ["release"].

Narrative / case study

  • Title format: pick a memorable one. X vs Y works; so does <famous-thing>, rebuilt in Semiotic.
  • Opening: state the comparison or the recreation in the first paragraph. Include the punchline. Don't bury it.
  • Why-care section: the reader is here because the topic is interesting independently of Semiotic. Lean into that. If you're rebuilding Minard's map, say what makes Minard's map the canonical example of data-viz composition. If you're comparing two chart types, say what makes the question "which one?" hard.
  • Multiple demos throughout. Comparative posts ideally show the two charts side-by-side or stacked.
  • Add a final h2 that lists 3–5 OTHER domains where the same story plays out. ("This pattern also shows up in pull-request lifecycle, supply-chain logistics, financial settlement, manufacturing rework.") The blog audience often isn't in the example domain; the cross-references are what make the post useful.
  • Tags: ["case-study", ...]. Add a family tag if the post is centered on one chart family.

OG card

Each entry produces a 1200×630 PNG at docs/public/blog/og/<slug>.png for social previews. Layout:

  • Left 2/3 — designed text: "Semiotic · BLOG" brand row, large title, subtitle, byline + date, tags row.
  • Right 1/3 — chart panel. When ogChart is set in metadata, the generator renders that chart via semiotic/server's renderChart and embeds the SVG. When omitted (release-summary posts, narrative posts without a single canonical chart), the panel renders a brand placeholder.

To add a chart preview:

js
ogChart: {
  component: "DifferenceChart",      // chart name as known to renderChart
  props: { /* optional overrides */ }
}

Supported chart components live in scripts/generate-blog-og-cards.mjs's OG_CHART_PRESETS. Add a new preset there if the chart you want isn't listed — preset fields are chartType + defaults (props object). The renderChart function only knows the chart families it has config for; check src/components/server/serverChartConfigs.ts to see what's supported. Charts not in renderChart (e.g. QuadrantChart, OrbitDiagram, AnscombesSankey, MinardsMarch) fall through to the brand-only card.

Run npm run generate:blog-og-cards after registering a new entry to refresh docs/public/blog/og/<slug>.png. The website build pipeline runs this automatically (it sits between generate:demo-gifs and parcel build in website:build).

SEO / pre-rendering

The blog inherits the docs' static-prerender path (scripts/prerender.mjs). For each blog entry, the script:

  • Reads metadata from docs/src/blog/entries-meta.js.
  • Writes docs/build/blog/<slug>/index.html with the title set to <entry-title> — Semiotic Blog.
  • Injects per-entry <meta name="description">, og:type=article, og:title, og:description, og:image (the rendered card PNG), article:published_time, article:author, per-tag article:tag, the full twitter:summary_large_image block, and a BlogPosting JSON-LD payload.

No additional wiring required — registering the entry in entries-meta.js is what the prerender script reads. Crawlers get a fully-resolved meta block; humans get the same SPA-loaded React experience.

Verification

Before declaring an entry done, run:

bash
# Typecheck
npm run typescript

# OG card generation
npm run generate:blog-og-cards

# Open in dev server after building the library
npm run website:start   # → http://localhost:3000/blog/<slug>/

Check that:

  • The entry appears in /blog/ (most recent in full, or in the preview list below).
  • The entry renders at /blog/<slug>/ with title, subtitle, byline, tags, and body content.
  • The OG card PNG was written and has the entry's title, subtitle, byline, and (if ogChart set) a rendered chart on the right.
  • The site builds: npm run website:build succeeds and docs/build/blog/<slug>/index.html has the entry-specific meta tags injected into <head>.

Template starter

A starter template is in templates/. Copy the shape that matches what you're writing:

  • templates/chart-explainer.js
  • templates/release-summary.js
  • templates/narrative.js

Each template has placeholder sections at the right heading levels and TODO comments at each spot the author needs to fill in. Use the templates as a checklist — every TODO needs an answer before publishing.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Blog Post AI skill do?

Author a new entry for the Semiotic blog. Use this skill whenever the user asks for a blog post, release summary, chart explainer, or case study to publish at /blog/SLUG.

Why use Blog Post on TypingMind?

Because you install it once and use it with any model. Blog Post is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blog Post in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nteract/semiotic/tree/main/.agents/skills/blog-post. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Blog Post?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blog Post?

As many as you like. As long as a model supports skills, you can use Blog Post with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blog Post AI skill free?

Yes. It is published on GitHub by nteract under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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