zhuge-logistics-illustrator
Skill0 starsChanged 3 months agoMITView on GitHub
Art-direct 16:9 Chinese logistics explainers with aligned process structures, short labels, restrained teal-green emphasis, a small guide character, source-aware claims, and publishing-size QA. Use for logistics education, supply-chain workflows, risk checks, comparisons, and operational knowledge cards.
In this repository4 other files it gives its agents.
- concise-writing-editorSkill
- legal-free-musicSkill
- visual-contentSkill
- xiaohei-article-illustratorSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 23
Write a shot card with nodes, arrows, hierarchy, exact Chinese labels, character summary, palette, source status, and alt text.
- Distinctive: line 24
Use a white 16:9 canvas, aligned peer nodes, restrained teal-green emphasis, and a small guide character only for the concluding …
- Distinctive: line 28
Do not turn an uncertain business claim into a definitive diagram.
- Distinctive: line 36
Verify reading order, peer-node alignment, edge meaning, labels, domain facts, exceptions, contrast, and cropping at publishing size.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Zhuge Logistics Illustrator
Designed, integrated, independently refactored, and continuously maintained by TIKAZ.
TIKAZ Edition
- Type: original domain illustration workflow; no upstream images or generator-specific assets are bundled.
- TIKAZ contribution: logistics claim decomposition, diagram grammar, alignment rules, character-summary role, source ledger, and factual/visual QA.
Inputs
Accept the logistics concept, audience, learning or decision goal, source facts, exceptions, publishing dimensions, exact labels, and preferred delivery format.
Workflow
- Identify the logistics concept, audience, decision or learning goal, and claims needing source verification.
- Select one diagram grammar: sequence, comparison, hub-and-spoke, layered system, risk checkpoint, or exception path.
- Write a shot card with nodes, arrows, hierarchy, exact Chinese labels, character summary, palette, source status, and alt text.
- Use a white 16:9 canvas, aligned peer nodes, restrained teal-green emphasis, and a small guide character only for the concluding explanation.
- Generate or draw with an available tool, then verify labels and domain facts against supplied or authoritative sources.
- Review at publishing size for reading order, alignment, edge meaning, contrast, cropping, factual accuracy, and accessible alternative text.
Do not turn an uncertain business claim into a definitive diagram. Mark assumptions and unresolved exceptions.
Output contract
Return the selected diagram grammar, node and edge contract, exact labels, exception paths, character summary, palette, source status, alt text, and final 16:9 asset or editable SVG/HTML specification.
Validation and fallback
Verify reading order, peer-node alignment, edge meaning, labels, domain facts, exceptions, contrast, and cropping at publishing size. If no visual creation tool is available, output an editable SVG/HTML plan or shot card. Keep uncertain facts visibly marked.
Example and limits
Use zhuge-logistics-illustrator to explain this warehouse exception flow as an editable 16:9 diagram with aligned nodes, verified Chinese labels, and alt text.Do not turn an uncertain business claim into a definitive diagram. Mark assumptions and unresolved exceptions.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

