media-heavy-workflows
Skill176 starsChanged 7 months agoMITView on GitHub
Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows. Use when those workflow concerns are central to the requested product. Do not use for individual canvas tools, ordinary image editing, one-off provider integrations, inference-runtime work, or simple image/video generation without a media workspace.
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 17
When users compare multiple generated candidates, keep batches and selection with their owning artifact.
- Distinctive: line 27
Verify only the changed behavior and risks: capability/reference handling, intended insertion or publish semantics, privacy, and secret …
- Very specific: line 32
Read references/media-studio-lessons.md only when the user actually requests cast boards, public/celebrity references, multi-provider …
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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
Media Heavy Workflows
Apply only the patterns required by the requested product; a media operation is not automatically a media studio.
Behavioral core
- Inspect the existing media entrypoint, ownership, provider route, and final insertion path. Preserve working behavior and the requested interaction.
- Distinguish saved references from references actually sent to a model. Honor the selected endpoint's supported tasks, input schema, and reference limits.
- When users compare multiple generated candidates, keep batches and selection with their owning artifact; snapshot the prompt, model, and references needed to explain each result.
- Separate generation from publishing only when the product requests a draft or review workflow. Direct image-edit actions may update their target immediately when undo and existing state semantics are preserved.
- Make external uploads and material cost visible. Keep provider credentials server-side, and require authorization before paid or irreversible actions.
- Show useful progress or failure state for slow operations. Preserve original dimensions and source ownership when the requested operation requires them.
- Verify only the changed behavior and risks: capability/reference handling, intended insertion or publish semantics, privacy, and secret protection.
Optional specialist guidance
Read references/media-studio-lessons.md only when the user actually requests
cast boards, public/celebrity references, multi-provider studios, structured
prompt authoring, specialized media-workspace layouts, or broader studio QA.
Those patterns are recommendations, not prerequisites for unrelated work.
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