alicloud-solution-content-article-illustrator

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Use when the user needs an end-to-end article illustration workflow in this repository that preserves Type x Style planning, loads article-illustration preferences, recommends Alibaba Cloud image backends, and produces a Markdown article with inserted local image references.

2installs
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NPX Install

npx skill4agent add cinience/alicloud-skills alicloud-solution-content-article-illustrator
Category: solution

Content Article Illustrator

Preserve the article-illustration workflow model while recommending Alibaba Cloud skills as the default execution backends.

Two Dimensions

DimensionControlsExamples
TypeInformation structureinfographic, scene, flowchart, comparison, framework, timeline
StyleVisual aestheticsnotion, warm, minimal, blueprint, watercolor, editorial

Validation

bash
mkdir -p output/alicloud-solution-content-article-illustrator
python3 tests/common/compile_skill_scripts.py \
  --skill-path skills/solutions/alicloud-solution-content-article-illustrator \
  --output output/alicloud-solution-content-article-illustrator/compile-check.json
Pass criteria: command exits 0 and
output/alicloud-solution-content-article-illustrator/compile-check.json
is generated with
"status": "pass"
.

Output And Evidence

  • Write workflow artifacts under
    output/alicloud-solution-content-article-illustrator/<topic-slug>/
    .
  • Save at least:
    source.md
    ,
    outline.md
    , one prompt file, generated images,
    article.with-images.md
    , and
    delivery-report.md
    .
  • Keep evidence for prompt-before-generation ordering and any edit pass used during repair.

Prerequisites

  • A source Markdown article.
  • A generation backend that satisfies
    references/backend-contract.md
    .
  • If you want repository-default behavior, prefer
    alicloud-ai-image-qwen-image
    and
    alicloud-ai-image-qwen-image-edit
    .
  • Optional
    EXTEND.md
    preferences at project or user scope.

Workflow

  1. Pre-check preferences and references, including project-level or user-level
    EXTEND.md
    .
  2. Analyze the source Markdown article and identify candidate illustration positions.
  3. Confirm settings in one batch: Type, Density, Style, optional Language, and output size.
  4. Choose or recommend a backend and build
    outline.md
    .
  5. Save prompt files before any generation step.
  6. Use the selected generation backend for first-pass images. Recommend
    alicloud-ai-image-qwen-image
    by default.
  7. If needed, use the selected edit backend for one repair pass per image. Recommend
    alicloud-ai-image-qwen-image-edit
    by default.
  8. Write
    article.with-images.md
    with relative
    images/...
    Markdown links.
  9. Save evidence and produce
    delivery-report.md
    .

Minimal Executable Run

bash
python3 skills/solutions/alicloud-solution-content-article-illustrator/scripts/run_workflow.py \
  --source path/to/article.md \
  --output-dir output/alicloud-solution-content-article-illustrator/example-run \
  --generation-backend mock

State Gates

  • drafted
    : source article and initial outline exist
  • confirmed
    : user settings, preferences, and backend choice are confirmed
  • generated
    : prompt files and first-pass images exist
  • validated
    : artifact structure and Markdown insertion pass checks
  • delivered
    : final article and report are written

References

  • Detailed workflow:
    references/workflow.md
  • Usage examples:
    references/usage.md
  • Style system:
    references/styles.md
  • Backend contract:
    references/backend-contract.md
  • Prompt construction rules:
    references/prompt-construction.md
  • Output contract:
    references/output-spec.md
  • Validation and test expectations:
    references/test-plan.md
  • Config setup:
    references/config/first-time-setup.md
  • Preferences schema:
    references/config/preferences-schema.md
  • Source references:
    references/sources.md
  • Helper scripts:
    scripts/load_preferences.py
    ,
    scripts/validate_inputs.py
    ,
    scripts/build_outline.py
    ,
    scripts/collect_evidence.py