feat(skills): add memento-flashcards optional skill (NousResearch#3827)

* feat(skills): add memento-flashcards skill

* docs(skills): clarify memento-flashcards interaction model

* fix: use HERMES_HOME env var for profile-safe data path

---------

Co-authored-by: Magnus Ahmad <magnus.ahmad@gmail.com>

Author: teknium1

optional-skills/productivity/memento-flashcards/SKILL.md

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+---
+name: memento-flashcards
+description: >-
+  Spaced-repetition flashcard system. Create cards from facts or text,
+  chat with flashcards using free-text answers graded by the agent,
+  generate quizzes from YouTube transcripts, review due cards with
+  adaptive scheduling, and export/import decks as CSV.
+version: 1.0.0
+author: Memento AI
+license: MIT
+platforms: [macos, linux]
+metadata:
+  hermes:
+    tags: [Education, Flashcards, Spaced Repetition, Learning, Quiz, YouTube]
+    requires_toolsets: [terminal]
+    category: productivity
+---
+
+# Memento Flashcards — Spaced-Repetition Flashcard Skill
+
+## Overview
+
+Memento gives you a local, file-based flashcard system with spaced-repetition scheduling.
+Users can chat with their flashcards by answering in free text and having the agent grade the response before scheduling the next review.
+Use it whenever the user wants to:
+
+- **Remember a fact** — turn any statement into a Q/A flashcard
+- **Study with spaced repetition** — review due cards with adaptive intervals and agent-graded free-text answers
+- **Quiz from a YouTube video** — fetch a transcript and generate a 5-question quiz
+- **Manage decks** — organise cards into collections, export/import CSV
+
+All card data lives in a single JSON file. No external API keys are required — you (the agent) generate flashcard content and quiz questions directly.
+
+User-facing response style for Memento Flashcards:
+- Use plain text only. Do not use Markdown formatting in replies to the user.
+- Keep review and quiz feedback brief and neutral. Avoid extra praise, pep, or long explanations.
+
+## When to Use
+
+Use this skill when the user wants to:
+- Save facts as flashcards for later review
+- Review due cards with spaced repetition
+- Generate a quiz from a YouTube video transcript
+- Import, export, inspect, or delete flashcard data
+
+Do not use this skill for general Q&A, coding help, or non-memory tasks.
+
+## Quick Reference
+
+| User intent | Action |
+|---|---|
+| "Remember that X" / "save this as a flashcard" | Generate a Q/A card, call `memento_cards.py add` |
+| Sends a fact without mentioning flashcards | Ask "Want me to save this as a Memento flashcard?" — only create if confirmed |
+| "Create a flashcard" | Ask for Q, A, collection; call `memento_cards.py add` |
+| "Review my cards" | Call `memento_cards.py due`, present cards one-by-one |
+| "Quiz me on [YouTube URL]" | Call `youtube_quiz.py fetch VIDEO_ID`, generate 5 questions, call `memento_cards.py add-quiz` |
+| "Export my cards" | Call `memento_cards.py export --output PATH` |
+| "Import cards from CSV" | Call `memento_cards.py import --file PATH --collection NAME` |
+| "Show my stats" | Call `memento_cards.py stats` |
+| "Delete a card" | Call `memento_cards.py delete --id ID` |
+| "Delete a collection" | Call `memento_cards.py delete-collection --collection NAME` |
+
+## Card Storage
+
+Cards are stored in a JSON file at:
+
+```
+~/.hermes/skills/productivity/memento-flashcards/data/cards.json
+```
+
+**Never edit this file directly.** Always use `memento_cards.py` subcommands. The script handles atomic writes (write to temp file, then rename) to prevent corruption.
+
+The file is created automatically on first use.
+
+## Procedure
+
+### Creating Cards from Facts
+
+### Activation Rules
+
+Not every factual statement should become a flashcard. Use this three-tier check:
+
+1. **Explicit intent** — the user mentions "memento", "flashcard", "remember this", "save this card", "add a card", or similar phrasing that clearly requests a flashcard → **create the card directly**, no confirmation needed.
+2. **Implicit intent** — the user sends a factual statement without mentioning flashcards (e.g. "The speed of light is 299,792 km/s") → **ask first**: "Want me to save this as a Memento flashcard?" Only create the card if the user confirms.
+3. **No intent** — the message is a coding task, a question, instructions, normal conversation, or anything that is clearly not a fact to memorize → **do NOT activate this skill at all**. Let other skills or default behavior handle it.
+
+When activation is confirmed (tier 1 directly, tier 2 after confirmation), generate a flashcard:
+
+**Step 1:** Turn the statement into a Q/A pair. Use this format internally:
+
+```
+Turn the factual statement into a front-back pair.
+Return exactly two lines:
+Q: <question text>
+A: <answer text>
+
+Statement: "{statement}"
+```
+
+Rules:
+- The question should test recall of the key fact
+- The answer should be concise and direct
+
+**Step 2:** Call the script to store the card:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add \
+  --question "What year did World War 2 end?" \
+  --answer "1945" \
+  --collection "History"
+```
+
+If the user doesn't specify a collection, use `"General"` as the default.
+
+The script outputs JSON confirming the created card.
+
+### Manual Card Creation
+
+When the user explicitly asks to create a flashcard, ask them for:
+1. The question (front of card)
+2. The answer (back of card)
+3. The collection name (optional — default to `"General"`)
+
+Then call `memento_cards.py add` as above.
+
+### Reviewing Due Cards
+
+When the user wants to review, fetch all due cards:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due
+```
+
+This returns a JSON array of cards where `next_review_at <= now`. If a collection filter is needed:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due --collection "History"
+```
+
+**Review flow (free-text grading):**
+
+Here is an example of the EXACT interaction pattern you must follow. The user answers, you grade them, tell them the correct answer, then rate the card.
+
+**Example interaction:**
+
+> **Agent:** What year did the Berlin Wall fall?
+>
+> **User:** 1991
+>
+> **Agent:** Not quite. The Berlin Wall fell in 1989. Next review is tomorrow.
+> *(agent calls: memento_cards.py rate --id ABC --rating hard --user-answer "1991")*
+>
+> Next question: Who was the first person to walk on the moon?
+
+**The rules:**
+
+1. Show only the question. Wait for the user to answer.
+2. After receiving their answer, compare it to the expected answer and grade it:
+   - **correct** → user got the key fact right (even if worded differently)
+   - **partial** → right track but missing the core detail
+   - **incorrect** → wrong or off-topic
+3. **You MUST tell the user the correct answer and how they did.** Keep it short and plain-text. Use this format:
+   - correct: "Correct. Answer: {answer}. Next review in 7 days."
+   - partial: "Close. Answer: {answer}. {what they missed}. Next review in 3 days."
+   - incorrect: "Not quite. Answer: {answer}. Next review tomorrow."
+4. Then call the rate command: correct→easy, partial→good, incorrect→hard.
+5. Then show the next question.
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py rate \
+  --id CARD_ID --rating easy --user-answer "what the user said"
+```
+
+**Never skip step 3.** The user must always see the correct answer and feedback before you move on.
+
+If no cards are due, tell the user: "No cards due for review right now. Check back later!"
+
+**Retire override:** At any point the user can say "retire this card" to permanently remove it from reviews. Use `--rating retire` for this.
+
+### Spaced Repetition Algorithm
+
+The rating determines the next review interval:
+
+| Rating | Interval | ease_streak | Status change |
+|---|---|---|---|
+| **hard** | +1 day | reset to 0 | stays learning |
+| **good** | +3 days | reset to 0 | stays learning |
+| **easy** | +7 days | +1 | if ease_streak >= 3 → retired |
+| **retire** | permanent | reset to 0 | → retired |
+
+- **learning**: card is actively in rotation
+- **retired**: card won't appear in reviews (user has mastered it or manually retired it)
+- Three consecutive "easy" ratings automatically retire a card
+
+### YouTube Quiz Generation
+
+When the user sends a YouTube URL and wants a quiz:
+
+**Step 1:** Extract the video ID from the URL (e.g. `dQw4w9WgXcQ` from `https://www.youtube.com/watch?v=dQw4w9WgXcQ`).
+
+**Step 2:** Fetch the transcript:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/youtube_quiz.py fetch VIDEO_ID
+```
+
+This returns `{"title": "...", "transcript": "..."}` or an error.
+
+If the script reports `missing_dependency`, tell the user to install it:
+```bash
+pip install youtube-transcript-api
+```
+
+**Step 3:** Generate 5 quiz questions from the transcript. Use these rules:
+
+```
+You are creating a 5-question quiz for a podcast episode.
+Return ONLY a JSON array with exactly 5 objects.
+Each object must contain keys 'question' and 'answer'.
+
+Selection criteria:
+- Prioritize important, surprising, or foundational facts.
+- Skip filler, obvious details, and facts that require heavy context.
+- Never return true/false questions.
+- Never ask only for a date.
+
+Question rules:
+- Each question must test exactly one discrete fact.
+- Use clear, unambiguous wording.
+- Prefer What, Who, How many, Which.
+- Avoid open-ended Describe or Explain prompts.
+
+Answer rules:
+- Each answer must be under 240 characters.
+- Lead with the answer itself, not preamble.
+- Add only minimal clarifying detail if needed.
+```
+
+Use the first 15,000 characters of the transcript as context. Generate the questions yourself (you are the LLM).
+
+**Step 4:** Validate the output is valid JSON with exactly 5 items, each having non-empty `question` and `answer` strings. If validation fails, retry once.
+
+**Step 5:** Store quiz cards:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add-quiz \
+  --video-id "VIDEO_ID" \
+  --questions '[{"question":"...","answer":"..."},...]' \
+  --collection "Quiz - Episode Title"
+```
+
+The script deduplicates by `video_id` — if cards for that video already exist, it skips creation and reports the existing cards.
+
+**Step 6:** Present questions one-by-one using the same free-text grading flow:
+1. Show "Question 1/5: ..." and wait for the user's answer. Never include the answer or any hint about revealing it.
+2. Wait for the user to answer in their own words
+3. Grade their answer using the grading prompt (see "Reviewing Due Cards" section)
+4. **IMPORTANT: You MUST reply to the user with feedback before doing anything else.** Show the grade, the correct answer, and when the card is next due. Do NOT silently skip to the next question. Keep it short and plain-text. Example: "Not quite. Answer: {answer}. Next review tomorrow."
+5. **After showing feedback**, call the rate command and then show the next question in the same message:
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py rate \
+  --id CARD_ID --rating easy --user-answer "what the user said"
+```
+6. Repeat. Every answer MUST receive visible feedback before the next question.
+
+### Export/Import CSV
+
+**Export:**
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py export \
+  --output ~/flashcards.csv
+```
+
+Produces a 3-column CSV: `question,answer,collection` (no header row).
+
+**Import:**
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py import \
+  --file ~/flashcards.csv \
+  --collection "Imported"
+```
+
+Reads a CSV with columns: question, answer, and optionally collection (column 3). If the collection column is missing, uses the `--collection` argument.
+
+### Statistics
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py stats
+```
+
+Returns JSON with:
+- `total`: total card count
+- `learning`: cards in active rotation
+- `retired`: mastered cards
+- `due_now`: cards due for review right now
+- `collections`: breakdown by collection name
+
+## Pitfalls
+
+- **Never edit `cards.json` directly** — always use the script subcommands to avoid corruption
+- **Transcript failures** — some YouTube videos have no English transcript or have transcripts disabled; inform the user and suggest another video
+- **Optional dependency** — `youtube_quiz.py` needs `youtube-transcript-api`; if missing, tell the user to run `pip install youtube-transcript-api`
+- **Large imports** — CSV imports with thousands of rows work fine but the JSON output may be verbose; summarize the result for the user
+- **Video ID extraction** — support both `youtube.com/watch?v=ID` and `youtu.be/ID` URL formats
+
+## Verification
+
+Verify the helper scripts directly:
+
+```bash
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py stats
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add --question "Capital of France?" --answer "Paris" --collection "General"
+python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due
+```
+
+If you are testing from the repo checkout, run:
+
+```bash
+pytest tests/skills/test_memento_cards.py tests/skills/test_youtube_quiz.py -q
+```
+
+Agent-level verification:
+- Start a review and confirm feedback is plain text, brief, and always includes the correct answer before the next card
+- Run a YouTube quiz flow and confirm each answer receives visible feedback before the next question