Context Engineering—Skills
Prompt Engineering
04 Nov 2025
Week ELEVEN
What are skills an example of?
Context engineering
Why use skills?
- Easy to set up
- progressive disclosure
- Saves tokens
- Attenuates context rot https://research.trychroma.com/context-rot
- Likely to be adopted by all frontier models
What are skills?
A skill is a package, fed to Claude as a zip file containing a folder structure. At a minimum, it contains a folder named for the skill with a file inside that folder called SKILL.md. Everything else is optional. Note that the SKILL.md file must be properly formatted as a markdown file with YAML frontmatter containing the fields name and description.
Skill structure
For example, it might contain a subfolder called scripts with Python or Bash scripts. It might contain additional context in a markdown file. It might contain data in a .csv file. None of this is read unless the prompt and the name or description field triggers it, saving tokens.
- name-of-skill/
- SKILL.md
- scripts/
- validate.py
- additional_context.md
- data.csv
What skills are built in to Claude?
Prepackaged skills
https://github.com/anthropics/skills I wanted more prepackaged skills to try, so I cloned the Anthropic Skills Repo
I asked Claude where to put it and it suggested ~/.anthropic/skills/
I checked the Claude documentation about where to put it and it suggested ~/.claude/skills/
It offered to make the directory and put the files there, by the way. This raises a typical problem for LLMs: it is typically faster to do a one-off task yourself rather than ask the LLM. The LLM (and Skills in particular) excel at automating repeated tasks.
Which skill to try?
Skill Creator is perhaps the most popular of Anthropic’s packaged skills, but I wanted something related to homework D, so I found a different repo through the following directory.
https://github.com/ComposioHQ/awesome-claude-skills?tab=readme-ov-file A list of some (allegedly) curated skills can be found here
I selected the CSV skill to try, since the data for hw D is in CSV format.
First I tried a built in example but it was a bit difficult to assess the results because I didn’t know the data.
The graphics it generated looked ridiculous on the face of it, but I needed to look at the data to be sure.
A ridiculous graphic
Another ridiculous graphic
Yet another ridiculous graphic
Visidata
Next, I tried looking at the data with Visidata, a cli tool I typically use for examining CSV files. Claude was helpful here, because it just had a three-letter month and four digit year in separate columns. Claude wrote a Python script to convert those into standard dates (the first of each month).
\(\langle\) Pause to view Visidata \(\rangle\)
Ames example
Next I tried the Ames data
It called a fairly good Python script to analyze the data but again produced ridiculous graphics.
\(\langle\) Pause to view Ames analysis \(\rangle\)
Can we fix these? Yes, if we know some Python, we can tell it what graphics to use. Even without knowing Python, we could limit the correlation heatmap to, say, the four most and least correlated variables.
On the other hand, if we know Python, it may be better (not faster as a one-off but better for routine use) to create our own Skill and Python script.
More about skills
https://news.ycombinator.com/item?id=45786738 discusses Claude Code in general but with an emphasis on Claude Skills.
END
References
Colophon
This slideshow was produced using quarto
Fonts are Roboto, Roboto Light, and Victor Mono Nerd Font
