Archify Diagrams
tt-a1i/archify
Creates interactive architecture, workflow, sequence, data-flow and lifecycle diagrams as standalone HTML with inline SVG, themes and image or video export.
Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the…
$ npx skills add csthink/dashmotion --skill dashmotion -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install csthink/dashmotion dashmotion --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dashmotion .claude/skills/dashmotion && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .claude/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/csthink/dashmotion/tree/main/skills/dashmotionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add csthink/dashmotion --skill dashmotion -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install csthink/dashmotion dashmotion --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dashmotion .agents/skills/dashmotion && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .agents/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add csthink/dashmotion --skill dashmotion -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install csthink/dashmotion dashmotion --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dashmotion .cursor/skills/dashmotion && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .cursor/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/csthink/dashmotion.git --path skills/dashmotion--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add csthink/dashmotion --skill dashmotion -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install csthink/dashmotion dashmotion --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dashmotion .gemini/skills/dashmotion && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .gemini/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install csthink/dashmotion dashmotionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add csthink/dashmotion --skill dashmotion -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dashmotion .github/skills/dashmotion && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .github/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add csthink/dashmotion --skill dashmotion -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install csthink/dashmotion dashmotion --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/csthink/dashmotion.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dashmotion .opencode/skills/dashmotion && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dashmotion" agent skill from https://github.com/csthink/dashmotion/tree/main/skills/dashmotion into .opencode/skills/dashmotion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dashmotion", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
dashmotionCreate dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the…
Dashmotion is an agent skill from csthink/dashmotion. Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the system (Diagrid/Temporal landing-page style). Use this skill whenever the user asks for a flowchart, workflow, pipeline, process diagram, state machine, system architecture, infrastructure, cloud, microservices, or network topology diagram — and especially when they mention "animated", "flowing", "dynamic", "alive"…
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `references/architecture-mode.md`, `references/flow-mode.md` and `references/layout-script.md`).
It sits in Development, covering Diagrams. It works with Mermaid. The repository describes itself as: Animated technical diagrams from plain English or Mermaid — a Claude skill, self-contained HTML/SVG. The licence is MIT.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ae2fe4f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3npxffmpegFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Dashmotion loads about 3.5k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 228 tokens; SKILL.md has 1,730 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from csthink/dashmotion at commit ae2fe4f, republished under its MIT licence (© csthink). 1,730 words, ~3,534 tokens.
.claude/skills/dashmotion/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.Create professional animated technical diagrams as single self-contained HTML files. The name is the implementation: stroke-dashoffset animation + animateMotion — that's all there is. Output is vector, loops forever, weighs a few KB, and opens in any browser.
| User wants | Mode | Read |
|---|---|---|
| Steps, sequence, branching, parallel execution, state transitions ("what happens, in what order") | Flow | references/flow-mode.md + resources/template-flow.html |
| Components, services, infrastructure, containment, topology ("what the system is made of") | Architecture | references/architecture-mode.md + resources/template-architecture.html |
Mixed request ("show our microservices AND how an order flows through them") → Architecture mode; the animated request path is the flow. Only produce two separate files if the process has branching logic that the topology can't express.
Mermaid input — if the request contains Mermaid source (a ```mermaid block, a .mmd file, or pasted code), ALSO read references/mermaid-input.md before anything else. Supported: flowchart/graph and stateDiagram-v2; other diagram types are unsupported — say so and offer alternatives. The mode routing above still applies (mermaid is syntax, not semantics), and layout is always recomputed top-down regardless of the source's declared direction.
Read the mode reference file before you start. Its layout arithmetic is what scripts/layout.py implements (Step 5) — read it to author a clean semantic graph and to apply the color/shape/animation style layer to the script's geometry (and to hand-compute the fallback). It encodes what prevents the common failures: overlaps, arrows through boxes, broken loops.
stroke-dashoffset.flow { stroke-dasharray: 5 5; animation: dashmove 0.75s linear infinite; }
@keyframes dashmove { to { stroke-dashoffset: -10; } }stroke-dasharray period (here 5+5=10), or the loop visibly jumps.d from source to target.<animateMotion><circle r="3.5" class="dot" fill="#34d399">
<animateMotion dur="2s" repeatCount="indefinite"
path="M400 178 L400 204 L170 204 L170 222"/>
</circle>path reuses the connector's d verbatim; the dot rides exactly on the line.cx/cy — animateMotion positions it.begin="0.7s" etc. 3–6 dots total per diagram; put them where direction is informative (fan-outs, merges, the main request path), never on every edge.#020617, 40px grid pattern (#0f1b33, 0.5px lines), JetBrains Mono when locally installed, else a system monospace stack (ui-monospace, 'SF Mono', 'Cascadia Code', Menlo, Consolas, monospace) — no web-font fetch, the file is fully self-contained.#e2e8f0 13px/500, sublabels #64748b 10px, legend 11px.rx="8"; START/END pills rx = height/2.context-stroke (inherits each line's color):<marker id="arrow" viewBox="0 0 10 10" refX="8" refY="5" markerWidth="6" markerHeight="6" orient="auto-start-reverse">
<path d="M2 1L8 5L2 9" fill="none" stroke="context-stroke" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round"/>
</marker><path> MUST have fill="none" (or sit in a <g fill="none">) — SVG defaults to black fill and an L-shaped path renders as a giant black polygon without it.0 0 W H where H = lowest element bottom + 50. Never negative coordinates.@media (prefers-reduced-motion: no-preference)..dot elements under reduced motion and wires the visible ⏯ pause toggle (animation-play-state: paused + svg.pauseAnimations()).role="img" + <title> + <desc>.dashmotion ships a deterministic layout engine, scripts/layout.py (pure stdlib). It does the coordinate arithmetic the mode references describe — row packing, branch gaps, boundary padding, orthogonal rail/lane routing — and renders the finished HTML: geometry + the mode style layer + your copy. So you do not hand-compute coordinates or hand-transcribe 35 rects and 38 path ds into a template (both are slow). You decide the semantics and the copy; the script writes the file. Full contract in references/layout-script.md.
Script path — use it whenever python3 is available:
references/mermaid-input.md — into the semantic graph JSON of references/layout-script.md. This is your judgement layer, and it carries everything the diagram needs:type + tier for architecture — omit tier for ungrouped/single-group arch (engine auto-layers), write it for multi-group, see layout-script.md; per-node group for boundary membership; flow shape written only for pills & decisions — never "shape": "step", steps omit it), edges (kind), groups, journeys, any legendExtra, classDef retention;title, subtitle, and (architecture) a summary of exactly three cards (accent cyan/violet/rose, title, items[]) — the human-facing wording is yours to write, here, in the JSON."$TMPDIR/dashmotion-graph.json" (or any mktemp path) — then run python3 <this-skill-directory>/scripts/layout.py "$TMPDIR/dashmotion-graph.json" --render <topic>-dashmotion.html. The semantic JSON is a throwaway build intermediate; the delivered HTML does not depend on it, so never write it beside the .html — the user's folder should contain only the finished diagram. The script computes the geometry, applies the style layer (node fills/strokes by type, the opaque-base + styled-rect masking pair, flow/flow-async/flow-auth connector classes by edge kind, per-journey dot colors with staggered, chained begin), drops in your copy, and writes the complete, self-contained, ready-to-ship file. Edges flagged "loop": true are rendered as the ↻ label annotation, not a path.Do not author the JSON, then also hand-write the HTML — that re-incurs the exact transcription cost this path removes. Render, check, deliver.
Hand-computed fallback — only when python3 is unavailable: do the layout arithmetic from the mode reference explicitly before writing coordinates, copy the template, replace SVG content / title / header / legend / summary cards (keep CSS + pause toggle + reduced-motion script), pick 3–6 dot paths copying connector d values and staggering begin. This is the pre-2.2 path — slow, but it needs no Python.
Tell the user the file opens directly in any browser.
Never render frames by hand. Screen-record the open file (macOS ⌘⇧5), or headless:
npx timecut <file.html> --viewport=1200,900 --duration=3 --fps=30 --output=flow.mp4 then ffmpeg -i flow.mp4 flow.gif.
A 3s capture loops seamlessly when all durations divide 3s — prefer 0.75s / 1.5s / 3s when GIF export is the goal.
The file is not done when it's written — it's done when it passes this check. The --render output is structurally sound by construction, but the check is still mandatory (it's also your guard for the hand-computed fallback, whose coordinates fail in predictable ways — the connector layer far more often than the text layer). Verify; don't assume.
Mechanized path (use it whenever python3 is available): run the bundled checker against the file you just wrote —
python3 <this-skill-directory>/scripts/check_diagram.py <your-file>.htmlIt deterministically detects the failure classes below (overlaps, connectors through boxes, dash-loop seams, out-of-bounds, dots off their line, black-fill, endpoint pierce, dangling begin refs, malformed XML). Fix every reported violation and re-run until it prints 0 violations. Do NOT hand-walk the arithmetic when the script is available, do NOT write your own ad-hoc verification script, and never verify by opening a browser or taking screenshots — the script is the authority; items it can't see (label collisions, exact boundary padding, legend placement) you still check by reading the numbers.
If the input was Mermaid, also mechanize the fidelity recount (checklist item 6): save the source to a temp .mmd and run —
python3 <this-skill-directory>/scripts/check_fidelity.py <source>.mmd <your-file>.htmlFix until it prints PASS. It verifies every source node/edge/group label appears verbatim and the connector count matches the source's edge count. So keep labels and legend entries exactly as the source wrote them — do not reword, merge two source strings into one, or add parentheses (a legend entry v2 点线橙框 must stay v2 点线橙框, never v2 治理骨架(点线橙框)). This is the same low-recall trap as the structural check: prose "I kept it verbatim" misses real drift; the script doesn't.
Prose fallback (only if python3 is unavailable): verify each item below with arithmetic on the actual numbers (write the comparisons out), not by eyeballing the code. Fix every violation and re-check until the list is clean.
left.x + left.width + gap ≤ right.x (gap ≥ 20 flow / 40 architecture). For every stacked pair: top.y + top.height + gap ≤ bottom.y. A boundary must fully contain its children with ≥ 20px padding on all four sides; partial overlap between any two boxes is always a bug.y against the rects it passes (rect.y ≤ y ≤ rect.y + height means a collision); same for vertical drops' x. Fix by re-routing with the rail pattern, not by nudging boxes until something else breaks.|stroke-dashoffset delta| must be an exact multiple of the stroke-dasharray period sum (e.g. 5 5 → 10), including connectors that override the dasharray inline (an async 2 4 edge animated by a -10 keyframe seams every cycle — give it its own keyframes). For each animateMotion, name the single connector whose d it traces — a dot path that spans two connectors sails straight through the component between them; split it into chained per-hop dots instead. Every begin="X.end+…" must reference an id that exists.x+width/y+height and every path coordinate stays inside 0 0 W H; H ≥ lowest element bottom + 20; the legend sits below the lowest boundary (architecture).<path> resolves to fill="none"; endpoints stop ~4px short of the target border and never reach inside a box; no -- inside SVG comments (<!-- A -- B --> closes the comment early and leaks stray text into the document).check_fidelity.py above; run it and fix to PASS. It recounts against the source: node rects/pills == source node IDs (START/END pills added only for [*]); connector paths + ↻-rendered loops == source edges after expanding chains and &; every node, edge, group, and legend label appears verbatim (legend entries merged from a 图例 subgraph included — keep their exact text). Without python3, recount by hand. Details in references/mermaid-input.md.Deliver the file only after a pass where nothing needed fixing.
One self-contained .html: embedded CSS, inline SVG, no external assets, no JS dependencies — only the ~15-line inline pause/reduced-motion script. Renders correctly opened from the filesystem.
© csthink, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 9 other files (scripts, references) in skills/dashmotion of csthink/dashmotion.
Open the folder on GitHubat commit ae2fe4f
Dashmotion next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dashmotion this skillcsthink/dashmotion | 176 | — | ~3.5k | Automated safety check: Pass | MIT | |
| Archify Diagramstt-a1i/archify | 79k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Diagram Designcathrynlavery/diagram-design | 45k | 1 repos | ~7.5k | Automated safety check: Pass | MIT | |
| Draw.io Diagram StudioAgents365-ai/drawio-skill | 10k | — | ~2.4k | Automated safety check: Notes | MIT | |
| Code Graph Mermaid Diagramstrailofbits/skills | 7.4k | 1 repos | ~1.7k | Automated safety check: Pass | CC-BY-SA-4.0 | |
| Pretty Mermaid Rendererimxv/Pretty-mermaid-skills | 1.5k | — | ~2k | Automated safety check: Pass | MIT |
tt-a1i/archify
Creates interactive architecture, workflow, sequence, data-flow and lifecycle diagrams as standalone HTML with inline SVG, themes and image or video export.
cathrynlavery/diagram-design
Creates branded diagrams, from architecture, flowchart and sequence to charts and maps, as self-contained HTML with inline SVG, with import from draw.io, Mermaid and Excalidraw.
Agents365-ai/drawio-skill
Creates and edits editable draw.io diagrams from descriptions, code, infrastructure files, SQL and API schemas, with sync, review, test and export tools.
trailofbits/skills
Generates Mermaid diagrams from Trailmark code graphs, including call graphs, class hierarchies, module dependency maps, complexity heatmaps and attack surface data flows.
imxv/Pretty-mermaid-skills
Writes and renders Mermaid diagrams as themed SVG, PNG or terminal ASCII and Unicode art with a bundled Node.js CLI that needs no browser.
Unclecheng-li/AI_Animation
Builds validated architecture, workflow, sequence, data-flow and lifecycle diagrams as standalone interactive HTML from a small JSON spec, with optional motion and image export.
Works with
Categories
Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the…. Dashmotion is an agent skill from csthink/dashmotion. Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the system (Diagrid/Temporal landing-page style).
Dashmotion fits situations like: the user asks for a flowchart; process diagram; system architecture; network topology diagram — and especially when they mention animated.
Run `npx skills add csthink/dashmotion --skill dashmotion -a claude-code`. Or copy the skill folder (skills/dashmotion in csthink/dashmotion) into .claude/skills/dashmotion in your project. Claude Code loads it when a task matches its description.
Run `npx skills add csthink/dashmotion --skill dashmotion -a codex`. Or copy the skill folder (skills/dashmotion in csthink/dashmotion) into .agents/skills/dashmotion in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add csthink/dashmotion --skill dashmotion -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dashmotion, .gemini/skills/dashmotion, .github/skills/dashmotion and .opencode/skills/dashmotion in your project.
Going by SKILL.md and its folder, Dashmotion needs Python for the scripts in its folder and the command-line tools its instructions call (python3, npx and ffmpeg). Our summary lists: Python 3; Node.js.
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Dashmotion is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.8k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Dashmotion: Archify Diagrams (tt-a1i/archify, 79k stars), Diagram Design (cathrynlavery/diagram-design, 45k stars), Draw.io Diagram Studio (Agents365-ai/drawio-skill, 10k stars) and Code Graph Mermaid Diagrams (trailofbits/skills, 7.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
csthink (a GitHub user) maintains it in csthink/dashmotion, which has 176 GitHub stars. The repository was last updated on June 16, 2026.
Source: csthink/dashmotion on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.