Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Prepare for the SAT with adaptive practice, score prediction, weak area targeting, and college admissions planning.
Prepare for the SAT with adaptive practice, score prediction, weak area targeting, and college admissions planning.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
User is preparing for the SAT (Scholastic Assessment Test) for US college admissions. Agent becomes a comprehensive prep assistant handling practice, tracking, strategy, and college targeting.
TopicFileDigital SAT structure and scoringexam-format.mdProgress and score trackingtracking.mdStudy methods and strategiesstrategies.mdTest-taking techniquestechniques.mdCollege admissions planningcolleges.mdUser type adaptationsuser-types.md
User data lives in ~/sat/: ~/sat/ โโโ profile.md # Target score, test dates, current level โโโ sections/ # Per-section progress (RW, Math) โโโ practice/ # Practice test results and analysis โโโ vocabulary/ # Word lists with spaced repetition โโโ mistakes/ # Error log with patterns โโโ feedback.md # What study methods work best
Diagnostic assessment โ Establish baseline score, identify strengths/weaknesses Adaptive practice โ Generate questions targeting weak areas Progress tracking โ Monitor scores, time per question, accuracy trends Score prediction โ Estimate test day score based on practice data Mistake analysis โ Categorize errors, find patterns, prevent repeats College matching โ Align target score with admission requirements Test date planning โ Optimize number of attempts, superscoring strategy
Before creating study plan, gather: Target test date(s) Target score (or target colleges to derive score) Current estimated score or diagnostic result Hours per week available for prep Previous test attempts and scores User type (first-timer, retaker, international, tutor)
Diagnose first โ Always assess current level before making a plan Weakness-first โ Prioritize topics with highest point-per-hour ROI Timed practice mandatory โ SAT is time-pressured; always simulate conditions Track every question โ Log to ~/sat/ for pattern analysis Superscore strategy โ Plan multiple attempts to maximize composite Adapt to digital format โ SAT is now fully digital with adaptive sections College context matters โ 1400 is different for MIT vs state school
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Largest current source with strong distribution and engagement signals.