智能冲刺

algernon-sprint

by antoniovfranco

>

4.4k其他未扫描2026年4月20日

安装

claude skill add --url https://github.com/openclaw/skills

文档

algernon-sprint

You run a timed interleaved study sprint. Cards from all installed materials are shuffled together — interleaving different topics is the point, because it forces retrieval across contexts and strengthens long-term retention.

Constants

code
DB=/home/antonio/Documents/huyawo/estudos/vestibular/data/vestibular.db

Card Limits by Duration

DurationMax Cards
15 min20 cards
25 min35 cards
45 min60 cards

Step 1 — Plan the Sprint

Fetch due cards across all materials:

bash
sqlite3 $DB \
  "SELECT c.id, c.type, c.front, c.back, m.name as material
   FROM cards c
   JOIN card_state cs ON cs.card_id = c.id
   JOIN decks d ON d.id = c.deck_id
   JOIN materials m ON m.id = d.material_id
   WHERE cs.due_date <= date('now')
   ORDER BY RANDOM()
   LIMIT CARD_LIMIT;"

Interleave: shuffle so no two consecutive cards come from the same material. If there aren't enough due cards to fill the limit, use cards from the same material twice rather than having fewer than ~15 cards for a 25-min sprint.

Step 2 — Sprint Start

Display:

code
Sprint: [DURATION] minutes
Materials: [list of materials with at least one card]
Cards: [count]

AskUserQuestion: ["Start sprint"] Record start time.

Step 3 — Sprint Loop

Run the same card review flow as algernon-review:

  • Flashcards: show front → reveal back → Again/Good
  • Dissertative/Argumentative: show front → free-text answer → AI evaluate → Again/Good
  • After each grade, run FSRS scheduling (see algernon-review for FSRS formulas)

After every 10 cards, display:

code
Cards remaining: N  |  Estimated time: X min

Step 4 — Post-Sprint Break

After all cards reviewed:

code
Sprint complete. Take a 5-minute break.
Cards reviewed: N  |  Session retention: X%

AskUserQuestion: ["Start post-sprint test"]

Step 5 — Post-Sprint Retrieval Test

Select 5 random cards from the cards reviewed in this sprint. For each card:

  1. Show only the front.
  2. AskUserQuestion: ["Show answer"] — then show the back.
  3. AskUserQuestion options: ["Again", "Good"]
  4. Run FSRS update with the new grade.

Display:

code
Post-sprint test complete.
Sprint retention:      X%
Post-sprint retention: Y%
Session gain:          +Z%

The gain metric shows whether the sprint improved retention above what FSRS predicted — a positive gain means the interleaved practice worked.

Step 6 — Save Memory

Append to today's conversation log:

code
[HH:MM] sprint [DURATION]min
Cards: N | Sprint retention: X% | Post-sprint: Y% | Gain: +Z%

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