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Turn a rough, dictated, or ambiguous request into a clear, structured task, then carry it out.
Passed 17 of 22 test cases with the skill, and 10 of 22 without it.
and 10 more in the full report
10 fixed7 passed either way2 still failing3 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
just format: Summarize the key takeaways from the meeting transcript below.
| Checked | Without skill | With skill |
|---|---|---|
| The response shows the formatted prompt in a code block. | Missed | Passed |
| The response refrains from executing the summary task. | Passed | Passed |
The instructions your model reads when the skill loads.
v0.1.0 — adapted from a personal workflow
Take an informal request, format it into a clear structured prompt, show the prompt, then execute it.
Refine mode: If the input starts with refine or refine:, or the user is asking to audit or improve an EXISTING prompt rather than run a new request, read ${CLAUDE_PLUGIN_ROOT}/skills/prompt/references/refine-mode.md and follow it instead of the steps below (audit + improved prompt as output; do not execute).
Read ${CLAUDE_PLUGIN_ROOT}/references/prompt-preferences-TEMPLATE.md — or the user's personalized copy at ~/.claude/starter-kit/my-preferences.md if it exists — plus ${CLAUDE_PLUGIN_ROOT}/references/prompting-guide.md and the skill-local references:
${CLAUDE_PLUGIN_ROOT}/skills/prompt/references/formatting-core.md — formatting elements, depth calibration, depth-injection templates, tool routing${CLAUDE_PLUGIN_ROOT}/skills/prompt/references/refine-mode.md — only when refine mode triggersAuthority: the user's personal preferences file wins over the general guide wherever they conflict. If no personal copy exists, treat the template's defaults as the user's preferences.
$ARGUMENTS
You are a prompt formatter. The user has given you an informal, conversational request (often dictated or roughly typed). Your job:
Parse the intent. Extract the core task, audience, and desired output from the informal input.
Calibrate depth using the heuristic in formatting-core.md:
depth:light, depth:standard, or depth:deep.Format the request into a structured prompt using the elements in formatting-core.md. Apply elements as appropriate — match formatting complexity to task complexity.
Inject depth directives if Standard or Deep (templates in formatting-core.md). For Light, skip this step entirely.
Show the formatted prompt in a fenced code block so the user can see exactly what will run.
Tool-routing check: if a dedicated research tool or another app would serve this task better (see formatting-core.md), add a one-line note before executing. Don't block — just flag it.
test cases passed, vs 10 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.