Internal subskill for carta-reporting. Exports Carta report data to a branded Excel file. Invoked by carta-reporting or carta-reporting-markdown when the user requests Excel output. Also the entry point when the main skill receives a message starting with "Generate Carta Excel —" (the artifact prompt bar payload).
carta-cap-table:6.91.7
Context expected from the calling skill (must be in session before this skill is invoked):
user_report_pk — needed to check for the cached report file and to fetch a fresh download URL if the file is absentcorporation_id — needed for call_tool({"name": "reporting__get__download_url", ...})carta-reporting-markdown (Claude Code)as_of_date, user full name — used as --title, --as-of-date, --generated-by args to excel_exporter.pyWhen the user pastes an artifact prompt bar payload, it arrives as a complete instruction starting with Generate Carta Excel —:
Generate Carta Excel —
Corporation: Meetly, Inc. (ID: 7)
Columns:
Equity Grants: columns: Grant ID, Award Type, Exercise Price; sorted by: Grant Date desc
Vesting Schedule: columns: Grant ID, Vest Date, Shares Vested; totals: Shares Vested sumUse the Corporation: line to confirm which company the export is for. Each indented line under Columns: is one sheet tab. This is always one Excel file with one tab per sheet. Parse each sheet line and pass all sheets to report_processor.py in a single run using the per-sheet sheets dict format. No further questions needed.
The column list from the artifact is authoritative; do not merge with or override it from the earlier conversation.
Parsing segment fields into report_processor.py config:
| Prompt bar field | report_processor.py per-sheet key |
|---|---|
columns: A, B, C | "columns": ["A", "B", "C"] |
sorted by: Col asc | "sort": [{"column": "Col", "direction": "asc"}] |
totals: Col sum, Col2 avg | "aggregations": {"type": "summary", "columns": {"Col": "sum", "Col2": "avg"}} |
totals: must become aggregations — this is the only way Excel formulas (=SUM(...), =AVERAGE(...)) are generated. If aggregations is omitted, any total rows in the output are hardcoded API values, not live formulas.
If the user asks for Excel without pasting a payload, ask: "Click the Excel export bar at the bottom of the artifact to select it, copy and paste it here — I'll generate the Excel with exactly those columns."
No scope context on this path. Entering fresh from the prompt bar, this skill cannot know
whether the account is share-class-scoped, so it cannot label a percentage column for the scope or
name the in-scope classes — the same limitation as label_overrides. The numbers are correct and
already scoped; only the labelling is generic. Do not describe any total as company-wide.
Use the column list confirmed during the Customization Checkpoint (resolved in carta-reporting-markdown).
Check if /tmp/carta_report_<user_report_pk>.json is available (use user_report_pk from this session):
"local_file" to report_processor.py.call_tool({"name": "reporting__get__download_url", "arguments": { user_report_pk, corporation_id }}) to get a fresh presigned URL and pass it as "download_url" instead.Always pipe through report_processor.py → excel_exporter.py, regardless of data size or complexity. Never write Excel files directly with openpyxl or any other library — the scripts handle Carta branding (logo, header, fonts, number formats) that will be missing from any ad-hoc implementation. This applies even when the dataset is small (e.g. 3 rows) or when sheets need to be combined.
For combining sheets into one tab, use merge_sheets in the report_processor.py call.
Pass all sheets in one run using the sheets dict. Pipe into excel_exporter.py. Reuse the cached _report_processor_path if the parent session resolved it (it may be unset on the fresh Generate Carta Excel — prompt-bar path — the find fallback handles that):
UV_PYTHON_DOWNLOADS=never uv run "${_report_processor_path:-$(find ~ -name "report_processor.py" -path "*/carta-reporting/scripts/*" 2>/dev/null | head -1)}" <<'EOF' | \
UV_PYTHON_DOWNLOADS=never uv run "$(find ~ -name "excel_exporter.py" -path "*/carta-reporting-excel/scripts/*" 2>/dev/null | head -1)" \
--title "Securities Ledger Report" \
--as-of-date 2024-01-15 \
--generated-by "Jane Doe" \
--output ./{report-slug}.xlsx
{
"local_file": "<path or use download_url if file not ready>",
"sheets": {
"Equity Grants": {"columns": ["Grant ID", "Award Type", "Exercise Price"],
"aggregations": {"type": "summary", "columns": {"Exercise Price": "sum"}}},
"Vesting Schedule": {"columns": ["Grant ID", "Vest Date", "Shares Vested"],
"sort": [{"column": "Vest Date", "direction": "asc"}]}
}
}
EOFThe script prints the absolute output path on success. Present it as a clickable link: computer://<absolute-path> (e.g. computer:///Users/jane/meetly-equity-grants.xlsx). Tell the user their file is ready to open, then offer next steps:
| Element | Value |
|---|---|
| Header background | #c6ebf4 |
| Header font | Arial 12pt bold, #2f3943 |
| Logo | <skill_base_dir>/assets/Carta_Logo.png, cell A2, 120×50px |
| Title | Cell B2, Arial 16pt bold |
| Subtitle | Cell B3, Arial 10pt, #666666 — "As of MMM d, yyyy • Generated with Claude AI by {user} at MMM d, yyyy h:mm:ss AM/PM TZ • Date format: MMM D, YYYY" |
| Header row | Row 5 with auto-filter; freeze panes at A6; data starts at row 6 |
Column type → number format: money → $#,##0.00 · percentage → 0.00% · integer → #,##0 · date → mmm d, yyyy · decimal → #,##0.0000
Column widths: string/date → 35, number types → 18.
2f20566
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