DeepSeek TUI Skills Examples

Questions this page should answer fast

What makes an example feel like a real skill rather than a fancy prompt?
Which repeated workflows deserve a dedicated skill first?
How do examples help you decide what to extract and what to leave as normal chat context?

What this page should help you decide

This page should help the reader spot reusable patterns, understand the anatomy of a good skills example, and decide when to keep a workflow as normal prompting instead.

Fast diagnosis

Repeated task

A good example starts from work that returns often enough to justify structure.

Stable boundary

The workflow should have a clear scope: what the skill does, what it does not do, and what inputs it expects.

Reusable defaults

The example should save time by encoding common assumptions, next steps, or checks that would otherwise be rewritten each time.

Step-by-step workflow

Start from repetition, not from elegance
Do not create a skill because the wording sounds impressive. Create it because the same workflow keeps returning.
Define the boundary clearly
A skill example becomes useful when a future session can tell where the skill starts, where it stops, and what remains human judgment.
Show what becomes easier
The best examples make one thing obviously cheaper: setup time, consistency, error checking, or context reuse.
Keep the example close to real work
Examples should look like something you would actually call from a terminal coding workflow, not like generic AI inspiration text.

Common mistakes

Calling any long prompt a skill even when it has no stable workflow boundary.
Writing examples that sound polished but do not save repeated work.
Forgetting to show why the example matters in a real terminal agent session.

When to leave this page

Leave this page once you can look at a repeated task and decide whether it deserves a reusable skill or should remain a one-off prompt.

Use-it-now examples

Start from working examples first, then adjust the details.

Start from one repeated terminal workflow

A useful example usually begins with a task you keep repeating, such as release-note drafting, repo triage, or structured code review.

# identify one task you repeat weekly
# define what stays the same each time

Write the boundary before the wording

A skill example becomes real once you can say what it owns, what it leaves to the operator, and what a successful run should hand back.

# define scope
# define stop point
# define expected output shape

Common failure branches

Work out which layer failed first instead of treating every problem as the same.

The example sounds good but saves no time

Then it is probably still just polished prompt text. Real skills reduce repeated setup or repeated decision overhead.

You cannot explain where the skill should stop

That means the boundary is too vague. Tighten scope before you try to keep it as a reusable asset.