great-tables-1-keep-tables-focused
Sub-skill of great-tables: 1. Keep Tables Focused (+3).
Best use case
great-tables-1-keep-tables-focused is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of great-tables: 1. Keep Tables Focused (+3).
Teams using great-tables-1-keep-tables-focused should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/1-keep-tables-focused/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How great-tables-1-keep-tables-focused Compares
| Feature / Agent | great-tables-1-keep-tables-focused | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of great-tables: 1. Keep Tables Focused (+3).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 1. Keep Tables Focused (+3)
## 1. Keep Tables Focused
```python
# GOOD: Select relevant columns
df_display = df[["Name", "Revenue", "Growth"]]
table = GT(df_display)
# AVOID: Displaying too many columns
# table = GT(df) # If df has 20+ columns
```
## 2. Use Appropriate Formatting
```python
# GOOD: Match format to data type
table = (
GT(df)
.fmt_currency(columns="Price", currency="USD")
.fmt_percent(columns="Growth", decimals=1)
.fmt_integer(columns="Units", use_seps=True)
)
# AVOID: Generic number format for everything
```
## 3. Limit Rows for Display
```python
# GOOD: Show summary or top N
df_top10 = df.nlargest(10, "Revenue")
table = GT(df_top10)
# AVOID: Displaying thousands of rows
```
## 4. Use Color Sparingly
```python
# GOOD: Highlight key information
table.data_color(
columns="Performance",
palette=["#fee2e2", "#dcfce7"], # Subtle colors
domain=[0, 100]
)
# AVOID: Rainbow color schemes
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