القائمة
Show ContextStellar scoring statistics, RLM learning progress, and grade distribution for the current project. Use when the user asks about their scoring stats, prompt quality trends, or RLM weight learning.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | stats |
| description | Show ContextStellar scoring statistics, RLM learning progress, and grade distribution for the current project. Use when the user asks about their scoring stats, prompt quality trends, or RLM weight learning. |
Show scoring statistics and RLM learning progress for the current project.
Check that CONTEXTSTELLAR_API_KEY is set. If not, tell the user to run /contextstellar:setup.
Fetch the shell stats (lightweight summary):
curl -s "${CONTEXTSTELLAR_BASE_URL:-https://contextstellar.com}/api/v1/hooks/shell-stats" \
-H "Authorization: ${CONTEXTSTELLAR_API_KEY}"
curl -s "${CONTEXTSTELLAR_BASE_URL:-https://contextstellar.com}/api/v1/hooks/stats?projectId=${CONTEXTSTELLAR_PROJECT_ID}" \
-H "Authorization: ${CONTEXTSTELLAR_API_KEY}"
Quick Summary (from shell-stats):
Detailed View (from full stats, if requested):
If RLM confidence is low (< 40%), suggest the user keep using Claude Code to accumulate more samples for better weight learning.
If the average score is below B, suggest running /contextstellar:optimize for improvement tips.
Analyze recent prompt patterns and suggest optimizations. Use when the user wants to improve their prompting patterns, reduce token costs, or see what the RLM flywheel has learned about their project.
Score a prompt for context engineering quality. Use when the user asks to score, analyze, or optimize a prompt, or when reviewing prompt quality before sending to an LLM.
Set up ContextStellar cloud mode for RLM learning and dashboards. Use when the user wants to configure an API key, connect their project, or upgrade from local-only scoring.