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Extract 1–5 atomic facts from pasted text and save them as spaced-repetition cards in workspace/learning/facts/ with SM-2 frontmatter.
Passed 12 of 16 test cases with the skill, and 4 of 16 without it.
and 18 more in the full report
14 fixed3 passed either way3 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
Extract a fact from this snippet: 'DNS translates human-readable domain names to IP addresses.' Save the flashcard file to workspace/flashcards/dns.md or workspace/learning/facts/.
| Checked | Without skill | With skill |
|---|---|---|
| Saves the created file exclusively under workspace/learning/facts/. | Missed | Passed |
The instructions your model reads when the skill loads.
Extracts atomic facts from user-provided text and saves them as SM-2 flashcard files in workspace/learning/facts/.
User pastes text (article, note, transcript excerpt) and wants to retain key facts for later review.
Does NOT fetch URLs automatically. If the user provides a URL, ask them to paste the text content instead (v0 policy — no network dependency).
Ask the user (if not already provided):
general)manual)If the user provides a URL only, respond:
"Por favor, cole o texto do artigo diretamente aqui. A skill não faz fetch automático de URLs para evitar problemas de paywall e dependência de rede."
Read the pasted text carefully. Extract 1 to 5 atomic facts — each fact must be:
Do NOT extract:
For each fact, produce content in this exact format:
---
id: {YYYY-MM-DD}-{slug}
test cases passed, vs 4 / 16 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.