Prompt to Skill
Takes a prompt someone runs over and over and packages it into a skill any agent can load, discover, and execute consistently. The costly mistake this prevents: transcribing the prompt verbatim into frontmatter, which preserves its padding and loses its triggers - producing a skill that neither fires nor performs.
Inputs to collect
- The prompt itself, verbatim - the real text they paste, not a summary of it.
- Two or three example runs: the input they gave and the output they liked. Real runs reveal what the prompt actually does versus what it says.
- What the prompt gets wrong today - the edits they make to its output every time. Those corrections become skill rules.
If the user cannot produce an example run, treat the request as a capability idea and hand off to skill-creator.
Operating procedure
Step 1 - Extract the pattern
Answer before writing anything:
- What is the one-sentence job this prompt does?
- What exact inputs does the user provide each run?
- What does a successful output look like, structurally?
- When would someone reach for this? Name three or more concrete trigger phrases in the user's own words.
If the prompt handles more than one job, split it: one skill per job. A prompt that "reviews my code and writes the commit message" is two skills.
Step 2 - Distill into the anatomy
Map the prompt onto the standard skill anatomy (see skill-author for the full standard):
- Procedural instructions become the numbered operating procedure.
- The inputs from Step 1 become the input-elicitation section.
- Heuristics and rules of thumb become concrete thresholds or if/then rules.
- The best example run becomes the worked artifact - keep one representative example, formatted as a good/bad pair if the user's corrections show what "bad" looked like.
- The user's recurring corrections become the Do NOT section. These are the highest-value lines in the whole skill: they encode failure modes the base model actually exhibits.
- The output description becomes the Deliverable section.
Drop prompt padding entirely: "please", "make sure to", "always remember", role-play framing ("you are an expert…"). Keep the rule, cut the filler.
Step 3 - Write the description last
Only after the body is settled, write the frontmatter description using the WHAT + WHEN + NOT formula (see skill-description-writer), quoting the trigger phrases from Step 1 verbatim. The description is what makes the skill fire; the trigger phrases came from the user, so use their words.
Step 4 - Verify against the original
Run the user's example input through the new skill mentally (or via skill-tester for a live check). The output must match or beat the output they liked. If it loses something the prompt had, a rule got dropped in distillation - find it and restore it as a rule, not as padding.
Quality bar
The conversion is done when: the skill fires on all three trigger phrases; every recurring correction the user reported is encoded as a Do NOT rule; the worked example survives from a real run; the body contains zero lines of prompt padding; and the user could delete their saved prompt without losing anything.
Do NOT
- Do not transcribe the prompt verbatim - distill it. Padding in a prompt is annoying; padding in a skill is a recurring token tax on every session.
- Do not invent triggers the user never said. Their real phrasing is the discoverability data; synthetic phrasing misses how they actually ask.
- Do not merge multiple jobs to keep one file. Two small precise skills beat one vague one.
- Do not skip the example run. A skill converted without evidence of what "good output" means is a guess wearing frontmatter.