| name | explore-entries |
| description | Builds the command to launch the interactive data explorer for the directory-pipeline.
Trigger this skill when the user asks "how do I explore the data", "open the explorer",
"view the entries", "create the HTML explorer", "browse the CSV", or mentions
`explore_entries.py`. The skill inspects the output directory to detect available
files and builds the right command with the correct flags for thumbnails, palette,
and translated variants.
|
When this skill is invoked, follow these steps exactly. Run all commands from the
project root directory.
Step 1: Ask which output to explore
Ask: "Which output directory or CSV file do you want to explore? For example:
output/green-book-1956/ or output/green-book-1956/entries_gemini-2.0-flash.csv."
Step 2: Resolve the target
If the user gave a directory path, use Glob to find entries CSV files:
- Pattern:
{output_dir}/entries_*.csv and {output_dir}/*/entries_*.csv
If multiple CSVs are found, list them and ask which to use. Common variants:
entries_{model}.csv — standard extractionentries_{model}_geocoded.csv — after geocodingentries_translated.csv — after translation
If the user gave a CSV path directly, use that.
Step 3: Check for supporting files
Use Glob to look for the following alongside the CSV (or in the output directory):
manifest.json — enables image thumbnails if presentpalette.json — auto-applied for color theming if present (no extra flag needed)*.jpg or *.jp2 — confirms images are local
Step 4: Build the command
Base command:
python -m pipeline.explore_entries output/{slug}/entries_{model}.csv
Add --output-dir for thumbnails: If manifest.json exists in output/{slug}/:
python -m pipeline.explore_entries output/{slug}/entries_{model}.csv \
--output-dir output/{slug}/
Without --output-dir, the explorer has no images. With it, entries that have
#xywh= in their canvas_fragment show cropped snippets; others show the full page.
Palette: If palette.json is found, tell the user: "A palette.json was
detected — color theming will be applied automatically."
Translated variant: If the user wants to explore a translated CSV:
python -m pipeline.explore_entries output/{slug}/entries_translated.csv \
--output-dir output/{slug}/
To create a translated CSV first, see the translation workflow (ask about /pipeline-run).
Step 5: Present the command and explain output
Show the complete command in a code block. Explain:
- Output is written to
output/{slug}/entries_{model}_explorer.html (or a name
derived from the CSV filename). Open in any browser — no server needed.
- The HTML file must stay in the same relative location as the output directory
for local image links to work correctly.
- If
canvas_fragment values contain #xywh= bounding boxes (from --align-ocr),
thumbnails are cropped to the exact entry region. Without alignment, the full
page is shown. To add bounding boxes, run --surya-ocr --align-ocr first.
- Color theming via
palette.json is applied automatically if the file is present — no extra flag needed.
