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// Generate presentation-grade decks, narratives, and speeches with audience adaptation
// Generate presentation-grade decks, narratives, and speeches with audience adaptation
[HINT] Download the complete skill directory including SKILL.md and all related files
| name | create |
| description | Generate presentation-grade decks, narratives, and speeches with audience adaptation |
| user-invocable | true |
| help | {"purpose":"Generate presentation-grade decks, narratives, speeches, and thought leadership content with audience adaptation.","use_cases":["Create a deck for [topic]","Write a speech for [event]","Draft a narrative for the board"],"scope":"presentations,decks,speeches,narratives,content"} |
/create is the TARS orchestrator for presentation-grade artifacts: decks, narratives, speeches, dashboards, memos. TARS owns content structuring, vault grounding, brand pointer, companion notes, telemetry, and filing. Office rendering delegates to Anthropic's first-party skills (pptx, docx, xlsx, pdf, web-artifacts-builder). TARS ships zero office-format libraries (no python-pptx, openpyxl, python-docx, weasyprint, markdown-it-py, matplotlib). See PRD ยง3.1b, ยง8.10, ยง26.4.
Vault reads/writes use mcp__tars_vault__* tools (see skills/core/SKILL.md). Data-source integrations (KPI, analytics, design, project tracker, documentation) resolve via mcp__tars_vault__resolve_capability(capability=โฆ).
When a resolve_capability call returns status: "unavailable", follow the degradation messaging convention in skills/core/SKILL.md section "Degradation messaging convention".
| Step | Name | Purpose |
|---|---|---|
| 0 | Capability probe | Detect which Anthropic rendering skills are available this session |
| 1 | Intake | Topic, audience, format, key messages, constraints |
| 2 | Brand auto-load | Resolve active brand file (tars-brand: true) for the rendering prompt |
| 3 | Context gathering | Initiatives, products, decisions, people, integration data |
| 4 | Format selection | Markdown only, or markdown + one/more Anthropic-rendered formats |
| 5 | Content-first draft | Structured markdown outline, saved + reviewed once |
| 6 | Review & approve | User confirms outline before render spend |
| 7 | Delegate render | Invoke chosen Anthropic skill(s) with brand pointer |
| 8 | Verify + companion | Confirm file exists, write .md companion per ยง26.13 |
| 9 | Telemetry | Emit artifact_generated |
On first /create invocation per session, detect which Anthropic first-party skills are available in this Claude Code install. Check the skill roster surfaced in <system-reminder> blocks or ask the host via the standard skill list โ do not attempt to load or probe the skill programmatically.
| Skill | Output format | Needed when |
|---|---|---|
pptx | .pptx | User requests a deck beyond Marp markdown |
docx | .docx | User requests Word output |
xlsx | .xlsx | User requests a spreadsheet |
pdf | .pdf | User requests PDF output |
web-artifacts-builder | HTML | User requests HTML / browser-renderable presentation |
Cache the detection result for the rest of the session. If a requested skill is missing, inform the user once with:
"Anthropic's
<skill>skill isn't available in this Claude Code install. Install it (it usually auto-bundles) or I can produce markdown / Marp output for now."
Fallback policy when a requested renderer is missing: produce markdown outline + (if a deck was requested) Marp-syntax markdown slides, and note the gap in the output.
Gather or infer:
If critical intake info is missing, apply the clarification protocol (batched multiple-choice, max 3โ4 per round).
Resolve the active brand guidelines file. Passed as a path pointer to the rendering skill in Step 7 โ TARS never theme-renders programmatically.
mcp__tars_vault__read_note(file="config") โ check frontmatter tars-active-brand.tars-brand: true.mcp__tars_vault__search_by_tag(tag="tars/brand"), filter results where frontmatter tars-brand: true.
update_frontmatter(file="config", property="tars-active-brand", value=<filename>).brand_file.See templates/brand-guidelines.md for the content shape that a brand file should follow.
Load relevant context via workspace MCP tools. .base views replace _index.md files in Obsidian mode.
mcp__tars_vault__search_by_tag(tag="tars/initiative", limit=20) + targeted read_note for those referenced.mcp__tars_vault__search_by_tag(tag="tars/product", limit=20) + targeted read_note.mcp__tars_vault__search_by_tag(tag="tars/decision", query="<topic keywords>", limit=10).mcp__tars_vault__read_note(file="<stakeholder name>") for audience-specific adaptation.mcp__tars_vault__semantic_search(scope="contexts", query=โฆ) when prose-heavy; otherwise search_by_tag + targeted reads.mcp__tars_vault__search_by_tag(tag="tars/journal", frontmatter={"tars-date__gte": โฆ}).Resolve capabilities before invoking their tools:
data_wh = mcp__tars_vault__resolve_capability(capability="data-warehouse")
analytics = mcp__tars_vault__resolve_capability(capability="analytics")
tracker = mcp__tars_vault__resolve_capability(capability="project-tracker")
design = mcp__tars_vault__resolve_capability(capability="design")
docs = mcp__tars_vault__resolve_capability(capability="documentation")
Skill degrades gracefully if any capability is unavailable. Record which data sources were used โ they feed tars-source-data on the companion note (ยง26.13).
Ask the user, gated on Step 0 capabilities:
Target output โ pick one or more:
1. Markdown only (always available, fastest)
2. PowerPoint deck (.pptx) [via anthropic pptx]
3. Word document (.docx) [via anthropic docx]
4. Excel workbook (.xlsx) [via anthropic xlsx]
5. PDF (.pdf) [via anthropic pdf]
6. HTML presentation [via anthropic web-artifacts-builder]
7. Marp-syntax markdown slides [always available; user renders locally]
Multiple allowed (e.g. "1+2" for markdown + pptx).
Grey-out / mark unavailable any option whose corresponding Anthropic skill failed the Step 0 probe. Default is markdown (#1).
Generate a structured markdown outline. Template starters live in templates/office/:
| Template | Shape |
|---|---|
deck-executive.md | Title / exec summary / 5โ10 content slides / appendix |
deck-narrative.md | Amazon six-pager style |
deck-technical-review.md | Background / options / recommendation / open questions |
spreadsheet-kpi-dashboard.md | Tabular outline (sheets, columns, sample rows) |
spreadsheet-roadmap.md | Swimlane grid of initiatives ร time |
doc-decision-memo.md | BLUF / context / options / recommendation |
doc-project-status.md | Health / milestones / risks / asks |
html-board-update.md | Single-page narrative with charts |
Populate the chosen outline with vault data. Per-slide / per-section structure:
## Slide 1: Title
**Key points:** โฆ
**Speaker notes:** โฆ
**Suggested visual:** โฆ
Save the outline:
mcp__tars_vault__create_note(
path="journal/YYYY-MM/YYYY-MM-DD-<slug>.md",
name="YYYY-MM-DD <Artifact Title>",
frontmatter={
"tags": ["tars/journal"],
"tars-date": "YYYY-MM-DD",
"tars-title": "<title>",
"tars-type": "deck | narrative | speech | spreadsheet",
"tars-audience": "Board | Conference | Team | <Stakeholder Name>",
"tars-topic": "<primary topic>",
"tars-initiatives": ["[[Related Initiative]]"],
"tars-output-formats": ["markdown", "pptx"],
"tars-brand-applied": "<brand-file-stem or 'none'>",
"tars-created": "YYYY-MM-DD"
},
body=<content outline markdown>
)
Present the outline (or a BLUF summary of it, if >50 slides / sections) and ask:
Proceed with render? (Review is free; render takes seconds-to-minutes per format.)
- "render" โ proceed with all formats selected in Step 4
- "render pptx" โ render a specific format only
- "edit <slide|section> N" โ revise before render
- "markdown only" โ stop here, keep only the outline
If only markdown was selected in Step 4, this step is a display-and-confirm, no render follows.
Invoke the chosen Anthropic skill(s) via the Claude Code skill-invocation mechanism. One invocation per format. Canonical prompt template:
I need the <pptx|docx|xlsx|pdf|web-artifacts-builder> skill to render the following content.
Content outline: <vault-relative path to the markdown saved in Step 5>
Output path: contexts/artifacts/YYYY-MM/<slug>.<ext>
Brand guidelines: <brand_file path from Step 2, or "none" if no brand>
Data sources used: <list from Step 3>
Vault context: TARS executive-assistant vault; match the executive-grade tone
described in the brand file (if any)
Companion note: DO NOT create a companion .md โ TARS will handle that after
you complete.
Proceed.
Wait for each render to complete. Do not fire them in parallel unless explicitly requested โ parallel invocations complicate companion-note ordering.
Note on brand: TARS passes the brand file path, not rendered theme artifacts. The rendering skill reads the file and applies the brand (LLM-driven). This is simpler, more flexible, and works for any brand + format.
For each rendered output:
mcp__tars_vault__read_note equivalent or filesystem probe via the rendering skill's own report)..md per ยง26.13 contract:mcp__tars_vault__create_note(
path="contexts/artifacts/YYYY-MM/<slug>.md",
name="<slug>.<ext>",
frontmatter={
"tags": ["tars/companion"],
"tars-companion-of": "<slug>.<ext>",
"tars-original-file": "<slug>.<ext>",
"tars-original-type": "pptx | docx | xlsx | pdf | html",
"tars-generated-by": "anthropic-skill:<pptx|docx|xlsx|pdf|web-artifacts-builder>",
"tars-orchestrated-by": "tars-create v3.1.0",
"tars-generated-at": "<ISO 8601>",
"tars-brand-applied": "<brand-file-stem or 'none'>",
"tars-source-initiative": "[[<initiative>]]",
"tars-source-data": [
{"capability": "data-warehouse", "server": "<resolved>", "query": "<query>"},
{"capability": "analytics", "server": "<resolved>", "path": "<path>"}
],
"tars-file-size": "<bytes>",
"tars-sha256": "<hex>",
"tars-created": "YYYY-MM-DD",
"tars-modified": "YYYY-MM-DD",
"tars-summary": "<1-paragraph narrative of what's in the artifact>"
},
body=<structure summary: slide list / section list / sheet list>
)
The companion note is discoverable via _views/all-documents.base.
Emit one event per rendered artifact:
{
"event": "artifact_generated",
"skill": "create",
"type": "deck|narrative|speech|spreadsheet|dashboard",
"format": "pptx|docx|xlsx|pdf|html|markdown|marp",
"renderer": "anthropic-skill:<name>|tars-markdown",
"brand_applied": true,
"data_sources": ["data-warehouse", "analytics"],
"outcome": "success|partial|error"
}
Emit skill_invoked + skill_completed at pipeline boundaries per ยง26.11.
| Audience type | Adaptation |
|---|---|
| Upstream (Board, CEO, CPO) | BLUF, ROI focus, concise, strategic framing |
| Downstream (Team) | Context-rich, motivating, clear RASCI |
| External (Conference, partners) | Thought leadership, industry framing, no internal jargon |
See skills/communicate/SKILL.md for the full Empathy Audit + RASCI rules when the artifact contains stakeholder language.
Strategic analysis light:
| Resource | Budget |
|---|---|
| Memory | up to 5 targeted files (stakeholders + initiatives + decisions) |
| Contexts | up to 3 reference documents |
| Journal | current month recent entries for freshness (โค2) |
| Integrations | parallel capability resolution; skip unavailable ones silently |
skills/communicate/.journal/YYYY-MM/ before invoking any render.contexts/artifacts/YYYY-MM/.artifact_generated telemetry per rendered output.