name	slideflow-yaml-authoring
description	Author and validate production-safe Slideflow YAML for Google Slides, Google Docs, Google Sheets, and local PowerPoint, including composable dbt connectors and AI providers.
version	2.0.0
spec	open-skill-v1

Slideflow YAML Authoring Skill

Purpose

Use this skill to produce production-safe Slideflow YAML and deterministic run commands across artifact kinds (slides, docs, sheets, powerpoint).

Supported provider ids:

google_slides
google_docs
powerpoint
google_sheets

Use this skill when

creating or editing Slideflow config for Google Slides, Docs, Sheets, or PowerPoint
translating reporting intent into data sources, transforms, replacements, and charts
selecting between template, plotly_go, and custom charts
defining AI summaries/replacements across providers (OpenAI, Gemini, Databricks serving)
validating provider contracts before runtime failures

Required inputs

target artifact kind (slides, docs, sheets, or powerpoint)
provider configuration (template id/folder ids/credentials behavior)
data source details (dbt/warehouse or direct sql/csv/json)
runtime parameter shape ({param} tokens and optional params CSV)
preferred AI provider (if AI summaries are required)

Deterministic workflow

Build the root contract for the artifact kind.
Define data sources with explicit names.
Prefer type: dbt + dbt: + warehouse: for new work.
Add replacements/charts (or workbook tabs for sheets) with explicit function names.
Validate references:
- $column references map to real output columns.
- every *_fn exists in function_registry.
- template ids/placeholders/markers are valid for provider.
Run commands from references/provider-command-matrix.md.
Run gotchas pass from references/gotchas.md.

Guardrails

Prefer additive, backward-compatible changes.
Keep legacy databricks_dbt examples clearly marked as legacy-only.
Keep secrets in env vars; never hardcode credentials/token values.
Use explicit template ids and registry paths when ambiguous.
For Databricks serving AI provider, use serving-endpoints base URL (not /invocations).
For Google Sheets, define tab mode intentionally (replace, append).
For citations-enabled slides configs, keep source metadata stable and deterministic.

Output contract

When producing config output, include:

complete YAML for the selected artifact kind
assumptions list (provider, runtime params, env vars)
exact doctor/validate/build commands
env var contract for data + AI provider
note on whether templates are built-in or local

References

references/config-schema-cheatsheet.md
references/provider-command-matrix.md
references/ai-provider-cheatsheet.md
references/citations.md
references/sheets-modes.md
references/template-authoring-contract.md
references/plotly-parameter-lookup.md
references/gotchas.md
assets/snippets/connectors.yml
assets/snippets/replacements.yml
assets/snippets/charts.yml
.github/skills/slideflow-yaml-authoring/assets/examples/

Slideflow YAML Authoring Skill

Purpose

Use this skill to produce production-safe Slideflow YAML and deterministic run commands across artifact kinds (slides, docs, sheets, powerpoint).

Supported provider ids:

google_slides

google_docs

powerpoint

google_sheets

Use this skill when

creating or editing Slideflow config for Google Slides, Docs, Sheets, or PowerPoint

translating reporting intent into data sources, transforms, replacements, and charts

selecting between template, plotly_go, and custom charts

defining AI summaries/replacements across providers (OpenAI, Gemini, Databricks serving)

validating provider contracts before runtime failures

Required inputs

target artifact kind (slides, docs, sheets, or powerpoint)

provider configuration (template id/folder ids/credentials behavior)

data source details (dbt/warehouse or direct sql/csv/json)

runtime parameter shape ({param} tokens and optional params CSV)

preferred AI provider (if AI summaries are required)

Deterministic workflow

Build the root contract for the artifact kind.

Define data sources with explicit names.

Prefer type: dbt + dbt: + warehouse: for new work.

Add replacements/charts (or workbook tabs for sheets) with explicit function names.

Validate references:

$column references map to real output columns.
every *_fn exists in function_registry.
template ids/placeholders/markers are valid for provider.

Run commands from references/provider-command-matrix.md.

Run gotchas pass from references/gotchas.md.

Guardrails

Prefer additive, backward-compatible changes.

Keep legacy databricks_dbt examples clearly marked as legacy-only.

Keep secrets in env vars; never hardcode credentials/token values.

Use explicit template ids and registry paths when ambiguous.

For Databricks serving AI provider, use serving-endpoints base URL (not /invocations).

For Google Sheets, define tab mode intentionally (replace, append).

For citations-enabled slides configs, keep source metadata stable and deterministic.

Output contract

When producing config output, include:

complete YAML for the selected artifact kind

assumptions list (provider, runtime params, env vars)

exact doctor/validate/build commands

env var contract for data + AI provider

note on whether templates are built-in or local

References

references/config-schema-cheatsheet.md

references/provider-command-matrix.md

references/ai-provider-cheatsheet.md

references/citations.md

references/sheets-modes.md

references/template-authoring-contract.md

references/plotly-parameter-lookup.md

references/gotchas.md

assets/snippets/connectors.yml

assets/snippets/replacements.yml

assets/snippets/charts.yml

.github/skills/slideflow-yaml-authoring/assets/examples/