nav-stats
Complete framework for context-efficient AI development - Philosophy, Metrics, Education, Skills, and Agents. Master context engineering principles through interactive learning. Achieve 92% token reduction with proven strategies.
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Navigator Session Statistics Skill
Show real-time efficiency reporting with baseline comparisons, making Navigator's value quantifiable and shareable.
When to Invoke
Invoke this skill when the user:
- Says "show my stats", "show session stats", "show metrics"
- Asks "how efficient am I?", "how much did I save?"
- Says "show my Navigator report", "efficiency report"
- Wants to see token savings or session performance
- Says "show impact", "prove Navigator works"
DO NOT invoke if:
- User just started session (< 5 messages)
- Navigator not initialized in project
- User asking about specific metrics only (answer directly)
Execution Steps
Step 1: Check Navigator Initialized
Verify Navigator is set up:
if [ ! -f ".agent/DEVELOPMENT-README.md" ]; then
echo "❌ Navigator not initialized in this project"
echo "Run 'Initialize Navigator' first"
exit 1
fi
Step 2: Run Enhanced Session Stats
Execute the enhanced session statistics script:
# Check if enhanced script exists
if [ ! -f "scripts/session-stats.sh" ]; then
echo "❌ Session stats script not found"
echo "This feature requires Navigator v3.5.0+"
exit 1
fi
# Run stats script
bash scripts/session-stats.sh
This script outputs shell-parseable variables:
BASELINE_TOKENS- Total size of all .agent/ docsLOADED_TOKENS- Actually loaded in session (estimated)TOKENS_SAVED- DifferenceSAVINGS_PERCENT- Percentage savedEFFICIENCY_SCORE- 0-100 scoreCACHE_EFFICIENCY- From OpenTelemetryCONTEXT_USAGE_PERCENT- Estimated context fillTIME_SAVED_MINUTES- Estimated time saved
Step 3: Calculate Efficiency Score
Use predefined function to calculate score:
# Extract metrics from session-stats.sh
source <(bash scripts/session-stats.sh)
# Calculate efficiency score using predefined function
EFFICIENCY_SCORE=$(python3 skills/nav-stats/functions/efficiency_scorer.py \
--tokens-saved-percent ${SAVINGS_PERCENT} \
--cache-efficiency ${CACHE_EFFICIENCY} \
--context-usage ${CONTEXT_USAGE_PERCENT})
Step 4: Format and Display Report
Use predefined function to format visual report:
# Generate formatted report
python3 skills/nav-stats/functions/report_formatter.py \
--baseline ${BASELINE_TOKENS} \
--loaded ${LOADED_TOKENS} \
--saved ${TOKENS_SAVED} \
--savings-percent ${SAVINGS_PERCENT} \
--cache-efficiency ${CACHE_EFFICIENCY} \
--context-usage ${CONTEXT_USAGE_PERCENT} \
--efficiency-score ${EFFICIENCY_SCORE} \
--time-saved ${TIME_SAVED_MINUTES}
Output Format:
╔══════════════════════════════════════════════════════╗
║ NAVIGATOR EFFICIENCY REPORT ║
╚══════════════════════════════════════════════════════╝
📊 TOKEN USAGE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Documentation loaded: 12,000 tokens
Baseline (all docs): 150,000 tokens
Tokens saved: 138,000 tokens (92% ↓)
💾 CACHE PERFORMANCE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Cache efficiency: 100.0% (perfect)
📈 SESSION METRICS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Context usage: 35% (excellent)
Efficiency score: 94/100 (excellent)
⏱️ TIME SAVED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Estimated time saved: ~42 minutes
💡 WHAT THIS MEANS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Navigator loaded 92% fewer tokens than loading all docs.
Your context window is 65% available for actual work.
🎯 RECOMMENDATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Excellent efficiency - keep using lazy-loading strategy
✅ Context usage healthy - plenty of room for work
Share your efficiency: Take a screenshot! #ContextEfficiency
Step 5: Add Context-Specific Recommendations
Based on efficiency score, provide actionable advice:
If efficiency_score < 70:
⚠️ RECOMMENDATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ Token savings below target (70%+)
→ Check: Are you loading more docs than needed?
→ Tip: Use navigator to find docs, don't load all upfront
Read more: .agent/philosophy/CONTEXT-EFFICIENCY.md
If context_usage > 80%:
⚠️ RECOMMENDATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ Context usage high (80%+)
→ Consider: Create context marker and compact
→ Tip: Compact after completing sub-tasks
Read more: .agent/philosophy/ANTI-PATTERNS.md
If cache_efficiency < 80%:
⚠️ RECOMMENDATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ Cache efficiency low (<80%)
→ Check: CLAUDE.md properly configured?
→ Tip: Ensure prompt caching enabled
Read more: .agent/philosophy/PATTERNS.md (Caching pattern)
Predefined Functions
efficiency_scorer.py
Calculate Navigator efficiency score (0-100) based on:
- Token savings (40 points)
- Cache efficiency (30 points)
- Context usage (30 points)
Usage:
python3 skills/nav-stats/functions/efficiency_scorer.py \
--tokens-saved-percent 92 \
--cache-efficiency 100 \
--context-usage 35
Output: 94 (integer score)
report_formatter.py
Format efficiency metrics into visual, shareable report.
Usage:
python3 skills/nav-stats/functions/report_formatter.py \
--baseline 150000 \
--loaded 12000 \
--saved 138000 \
--savings-percent 92 \
--cache-efficiency 100 \
--context-usage 35 \
--efficiency-score 94 \
--time-saved 42
Output: Formatted ASCII report (see Step 4)
Philosophy Integration
Context Engineering Principle: Measurement validates optimization
From .agent/philosophy/PATTERNS.md:
"Measure to validate. Navigator tracks real metrics, not estimates."
This skill proves:
- Token savings are real (baseline comparison)
- Cache efficiency works (OpenTelemetry data)
- Context usage is healthy (window not overloaded)
- Time saved is quantifiable (6s per 1k tokens)
User Experience
User says: "Show my stats"
Skill displays:
- Visual efficiency report
- Clear metrics (tokens, cache, context)
- Interpretation ("What this means")
- Actionable recommendations
User can:
- Screenshot and share (#ContextEfficiency)
- Understand Navigator's impact
- Optimize workflow based on recommendations
- Validate context engineering principles
Example Output Scenarios
Scenario 1: Excellent Efficiency (Score 94)
User following lazy-loading pattern, cache working perfectly:
- 92% token savings ✅
- 100% cache efficiency ✅
- 35% context usage ✅
- Score: 94/100
Recommendation: Keep it up! Share your efficiency.
Scenario 2: Fair Efficiency (Score 72)
User loading too many docs upfront:
- 65% token savings ⚠️
- 95% cache efficiency ✅
- 55% context usage ✅
- Score: 72/100
Recommendation: Review lazy-loading strategy. Load docs on-demand.
Scenario 3: Poor Efficiency (Score 48)
User not using Navigator patterns:
- 45% token savings ❌
- 70% cache efficiency ⚠️
- 85% context usage ❌
- Score: 48/100
Recommendation: Read philosophy docs. Consider /nav:compact. Review CLAUDE.md.
Success Metrics
After using this skill, users should:
- Understand their efficiency score
- See quantified token savings
- Know what to improve (if anything)
- Feel motivated to share results
Long-term impact:
- Users screenshot reports and share
- "Navigator saved me 138k tokens" becomes common
- Efficiency becomes visible, not abstract
- Continuous improvement through measurement
This skill makes Navigator's value tangible and shareable.
