learn-capture

# Learn Capture Extracts atomic facts from user-provided text and saves them as SM-2 flashcard files in `workspace/learning/facts/`. ## Trigger 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). ## Workflow ### Step 1 — Receive input Ask the user (if not already provided): - The text to capture (paste directly) - Optional: deck name (default: infer from content or use `general`) - Optional: source URL or description (default: `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." ### Step 2 — Extract facts Read the pasted text carefully. Extract **1 to 5 atomic facts** — each fact must be: - **Atomic:** one idea per fact, not a summary paragraph - **Memorable:** something worth reviewing in 1–30 days - **Retrievable:** can be turned into a self-test question Do NOT extract: - Opinions without evidence - Context that depends on reading the full article - Facts already trivially known (e.g., "Python is a programming language") ### Step 3 — Generate file content for each fact For each fact, produce content in this exact format: ```markdown --- id: {YYYY-MM-DD}-{slug} source: {source_url_or_"manual"} deck: {deck_name} created: {YYYY-MM-DD} next_review: {YYYY-MM-DD+1 day} interval: 1 ease: 2.5 reps: 0 lapses: 0 --- **Fact:** {The atomic fact stated directly, in pt-BR.} **Why it matters:** {One sentence on why Davidson should remember this, in pt-BR.} **Retrieval Q:** {A question whose answer is the fact above, in pt-BR.} ``` **Slug rules:** - Kebab-case of the main topic of the fact - Max 40 characters - No accents, special characters, or spaces - Example: `claude-skills-sao-arquivos-markdown` **If slug collision (same date + same slug):** append `-2`, `-3`, etc. **Dates (use today's actual date):** - `created`: today in YYYY-MM-DD - `next_review`: tomorrow in YYYY-MM-DD (today + 1 day) **Language:** fact content (Fact, Why it matters, Retrieval Q) must be in **pt-BR** by default (workspace.language = pt-BR), regardless of the source language. ### Step 4 — Save files For each fact: 1. Create `workspace/learning/facts/` directory if it does not exist 2. Write the file to `workspace/learning/facts/{YYYY-MM-DD}-{slug}.md` 3. Confirm success with the file path ### Step 5 — Report After saving all files, output a summary: ``` ✅ {N} fato(s) capturado(s) no deck "{deck}": - workspace/learning/facts/{filename1}.md → {first 5 words of Retrieval Q}... - workspace/learning/facts/{filename2}.md → ... ``` ## Constraints - Max 5 facts per capture session. If the text warrants more, tell the user to split it into multiple runs. - Do NOT create or modify any file outside `workspace/learning/facts/`. - Do NOT touch `review-log.jsonl` or any existing fact file. - Do NOT fetch URLs — ask user to paste text. - All 9 frontmatter fields must be present: `id`, `source`, `deck`, `created`, `next_review`, `interval`, `ease`, `reps`, `lapses`. - `interval=1`, `ease=2.5`, `reps=0`, `lapses=0` are always the initial values.