Chapter 30: Preparing for Origin
Lin Feng woke at 4:30 AM on Tuesday, two hours before his alarm. His mind was already processing Green Valley data, running through beast behavior patterns, calculating optimal engagement strategies.
Sleep was impossible now.
He grabbed his tablet and pulled up the academy's Beast Database—a comprehensive archive of Land of Origin creatures compiled from decades of observation and combat reports. The database contained far more detail than the basic briefing packet.
GREEN VALLEY BEAST DATABASE - DETAILED STUDY
Lin Feng started with Tier 1 Rabbit Beasts, since they comprised 60% of expected encounters.
TIER 1 RABBIT BEAST - COMPREHENSIVE ANALYSIS
Physical Characteristics:
Average height: 2.1 meters Weight: 95-110 kilograms Hind leg muscle density: Exceptional (enables 8-meter vertical leaps) Dental structure: 18 sharp teeth, jaw pressure 450 PSI Fur coloration: Gray-brown with white underbelly Eye placement: Lateral (270-degree vision, poor depth perception directly ahead)
Behavioral Patterns:
Territorial: Defend 200-meter radius around den sites Aggression trigger: Movement within 50 meters Attack preference: Frontal lunge using hind legs Retreat threshold: After sustaining 30% health damage Pack behavior: Occasionally pair-hunt (15% of encounters) Activity cycle: Primarily diurnal, 70% active during daylight hours
Combat Statistics:
Energy signature: 80-120 units Attack damage: 35-45 units per successful lunge Attack frequency: 4-second intervals between lunges Movement speed: 12 meters/second in straight line, 6 meters/second lateral Dodge capability: Poor (commits fully to attack vectors) Durability: 180-220 total health
Tactical Vulnerabilities:
Poor mid-air directional control during lunge attacks 1.2-second recovery period after landing Weak armor on underbelly and neck Poor peripheral awareness when focused on single target Predictable attack angle (always lunges directly toward target)
Lin Feng entered his soul space and began programming this detailed data into his Analysis Protocol. The system needed precise parameters to generate accurate tactical recommendations.
RABBIT BEAST COMBAT ALGORITHM - CODING IN PROGRESS
He created decision trees based on the behavioral data:
IF rabbit beast detected at 50+ meters THEN maintain defensive stance and prepare intercept
IF rabbit beast lunges from 0-15 degrees angle THEN sidestep left and counter-attack during recovery
IF rabbit beast lunges from 15-45 degrees THEN shield deflection at 30-degree angle to redirect momentum
IF rabbit beast health below 30% THEN predict retreat behavior and prepare pursuit or disengage
IF two rabbit beasts detected THEN prioritize the closer target, maintain awareness of second threat
The algorithm grew more sophisticated as he added layers of conditional logic. Attack patterns at different energy levels, behavioral variations in forest versus grassland terrain, pack coordination tendencies, retreat path predictions.
Three hours of coding later, Lin Feng had a comprehensive tactical model.
RABBIT BEAST TACTICAL MODEL COMPLETE
DECISION BRANCHES: 37
RESPONSE PROTOCOLS: 84
PREDICTED ACCURACY: 88% (SIMULATION TESTED)
He moved to Tier 1 Scorpion Beasts next.
TIER 1 SCORPION BEAST - COMPREHENSIVE ANALYSIS
Physical Characteristics:
Body length: 3.2 meters (including tail) Weight: 140-165 kilograms Exoskeleton armor: Hard chitin, resistant to slashing attacks Tail stinger: 40-centimeter length, poison delivery system Claw strength: Can crush 2-centimeter steel Leg structure: Eight legs, stable on rocky terrain Sensory organs: Vibration detection through ground, poor visual acuity
Behavioral Patterns:
Territorial: Defend elevated positions (rock formations, hills) Engagement range: Prefers 20-30 meters distance Attack pattern: Ranged stinger projectiles (poison-coated bone spikes) Melee defense: Claw attacks if enemies close within 5 meters Retreat behavior: Backs toward elevated terrain when threatened Activity cycle: Nocturnal preference but active in shaded areas during day
Combat Statistics:
Energy signature: 90-130 units Stinger damage: 25-35 units per hit (plus poison effect) Poison effect: 5 units/second for 30 seconds if untreated Attack frequency: 8-second reload time between stinger shots Stinger range: Maximum 35 meters, accurate to 25 meters Stinger velocity: 18 meters/second Durability: 200-240 total health Weak points: Joints between exoskeleton segments, underside
Tactical Vulnerabilities:
Extremely poor mobility (3 meters/second maximum) Predictable territorial behavior (rarely leaves elevated position) Long reload time between ranged attacks creates engagement windows Vulnerable to flanking attacks (slow rotation speed) Exoskeleton weak to piercing attacks at segment joints Poor close-range combat effectiveness
Lin Feng coded the Scorpion behavioral model with emphasis on the ranged attack patterns.
SCORPION BEAST COMBAT ALGORITHM - CODING IN PROGRESS
IF scorpion detected on elevated position THEN calculate stinger trajectory prediction
IF stinger fired THEN dodge timing = 1.4 seconds (projectile travel time at 25 meters)
IF stinger dodged THEN advance during 8-second reload window
IF close combat range (<5 meters) achieved THEN attack segment joints with piercing strikes
IF multiple scorpions on same outcrop THEN engage from flanking angle to limit simultaneous fire
The Scorpion model was simpler than the Rabbit model—the beasts were less mobile and more predictable. But the poison mechanic required careful programming. The Analysis Protocol needed to track poison duration and recommend priority healing from Tang Yue if anyone was hit.
SCORPION BEAST TACTICAL MODEL COMPLETE
DECISION BRANCHES: 28
RESPONSE PROTOCOLS: 61
POISON TREATMENT PROTOCOL: INTEGRATED
PREDICTED ACCURACY: 91% (SIMULATION TESTED)
Finally, Lin Feng tackled the most complex model: Tier 2 Wolf Beasts.
TIER 2 WOLF BEAST - COMPREHENSIVE ANALYSIS
Physical Characteristics:
Height at shoulder: 1.8 meters Body length: 2.6 meters Weight: 180-220 kilograms Jaw strength: 1,200 PSI bite force Claw length: 8 centimeters, razor-sharp Fur: Thick gray-black, provides minor damage resistance Pack hierarchy: Alpha (largest), Betas (followers)
Behavioral Patterns:
Pack coordination: 3-5 wolves per pack, highly organized Alpha role: Directs pack tactics through howls and body language Beta role: Execute flanking maneuvers, follow alpha commands Hunting strategy: Surround prey, alternate attacks to exhaust target Communication: Howls signal tactical adjustments Retreat threshold: Pack scatters if alpha is killed Territory size: 2-kilometer range per pack
Combat Statistics (per wolf):
Energy signature: 300-400 units (Alpha: 400-500 units) Bite damage: 60-75 units Claw damage: 40-50 units Attack frequency: 3-second intervals Movement speed: 15 meters/second sprint, 8 meters/second sustained Durability: 450-550 total health (Alpha: 600-700) Intelligence: High (Tier 2 cognitive capacity)
Pack Tactics:
Pincer formation: Betas flank from sides while alpha attacks front Rotation attack: Wolves take turns engaging to prevent target from focusing Exhaustion strategy: Maintain pressure until prey energy depletes Adaptive behavior: Adjust tactics based on prey responses Communication signals: Single howl = advance Double howl = flank maneuver Triple howl = retreat
Tactical Vulnerabilities:
Pack coordination dependent on alpha survival Predictable communication signals reveal tactical intent Individual wolves vulnerable when isolated from pack Flanking maneuvers create temporary positional weaknesses Energy-intensive tactics deplete wolf stamina over extended engagements
This model required the most sophisticated programming. Pack coordination meant tracking multiple enemies simultaneously, predicting tactical shifts based on alpha communication, identifying optimal alpha-elimination opportunities.
WOLF PACK COMBAT ALGORITHM - CODING IN PROGRESS
Lin Feng spent five hours building the wolf pack tactical model. The complexity was substantial—he needed algorithms for:
Pack formation recognition (pincer, rotation, exhaustion patterns)
Alpha identification through behavioral analysis (larger size, central position, command howls)
Communication signal interpretation (howl patterns indicate tactical shifts)
Focus-fire coordination (concentrate team attacks on alpha target)
Isolation tactics (separate individual wolves from pack support)
Adaptive counter-tactics (respond to pack tactical adjustments)
The wolf model integrated with team coordination protocols more deeply than the other beast models. Fighting a coordinated enemy required coordinated response.
WOLF PACK TACTICAL MODEL COMPLETE
DECISION BRANCHES: 64
RESPONSE PROTOCOLS: 143
PACK COORDINATION COUNTER-ALGORITHMS: 23
PREDICTED ACCURACY: 76% (SIMULATION TESTED, LOWER DUE TO HIGH ENEMY INTELLIGENCE)
By the time Lin Feng finished all three beast models, it was Tuesday afternoon. He'd spent nearly twelve hours coding, but the Analysis Protocol now contained comprehensive tactical databases for every common Green Valley threat.
BEAST DATABASE - COMPLETE STATUS
TIER 1 RABBIT BEAST: 88% PREDICTED ACCURACY
TIER 1 SCORPION BEAST: 91% PREDICTED ACCURACY
TIER 2 WOLF PACK: 76% PREDICTED ACCURACY
TOTAL DECISION BRANCHES: 129
TOTAL RESPONSE PROTOCOLS: 288
INTEGRATED WITH TEAM COORDINATION SYSTEMS
Wednesday brought the next phase of preparation: studying terrain and drop tables.
Lin Feng accessed the academy's Geographic Database for Green Valley Zone. The database contained topographical data, vegetation surveys, water source locations, and historical encounter density maps.
GREEN VALLEY TERRAIN - DETAILED STUDY
He downloaded high-resolution terrain maps and began analyzing tactical implications.
EASTERN FOREST SECTOR:
Vegetation density: 85% canopy coverage Tree spacing: 3-5 meters average Undergrowth: Moderate, limits visibility to 15 meters Elevation change: Minimal (120-150 meters) Water sources: Two small streams Beast density: HIGH (Rabbit Beasts prefer forest terrain) Tactical notes: Limited maneuvering space, close-quarters combat likely, poor sightlines for Scorpion ranged attacks
SOUTHERN GRASSLAND SECTOR:
Vegetation: Open grassland, 30% coverage Visibility: Excellent, 200+ meters in clear conditions Elevation change: Gentle slopes (150-180 meters) Water source: One stream bordering forest edge Beast density: MODERATE (mixed encounters) Tactical notes: Excellent visibility aids threat detection, open terrain favors mobility, vulnerable to Wolf pack flanking
ROCKY OUTCROP AREAS:
Distribution: Scattered throughout valley, 10% total area Height: 5-15 meters elevation Stability: Generally stable, some loose rocks Beast density: HIGH for Scorpions (preferred habitat) Tactical notes: Elevated positions favor ranged enemies, climbing required for engagement, fall hazards present
NORTHERN RIDGE (RESTRICTED ZONE):
Elevation: 280-340 meters Terrain: Steep, rocky, dense vegetation Beast density: EXTREME (Tier 3 Bear territory) Tactical notes: AVOID ENTIRELY per authorization restrictions
Lin Feng programmed the terrain data into his Analysis Protocol, creating overlays that combined beast behavior with environmental factors.
IF Rabbit Beast encounter in Eastern Forest THEN recommend close-quarters deflection tactics using trees as obstacles
IF Scorpion encounter on rocky outcrop THEN calculate optimal climbing approach to minimize exposure to stinger fire
IF Wolf pack in Southern Grassland THEN recommend defensive formation to prevent flanking in open terrain
The terrain database integrated seamlessly with the beast behavioral models, creating compound tactical recommendations based on both enemy type and environmental context.
TERRAIN DATABASE INTEGRATION COMPLETE
ENVIRONMENTAL FACTORS: 47 CODED
TERRAIN-SPECIFIC TACTICS: 82 GENERATED
Next, Lin Feng studied equipment drop tables.
GREEN VALLEY EQUIPMENT DROP ANALYSIS
The database contained statistical data from thousands of student operations over multiple years.
TIER 1 RABBIT BEAST DROPS:
Chaos Crystal (Colorless): 25% drop rate Leg Component (Colorless): 3% drop rate Leg Component (White): 1% drop rate Claw Weapon Attachment (Colorless): 1% drop rate Nothing: 70% encounters
TIER 1 SCORPION BEAST DROPS:
Chaos Crystal (Colorless): 20% drop rate Armor Component (Colorless): 4% drop rate Armor Component (White): 2% drop rate Poison Resistance Module (White): 2% drop rate (RARE) Stinger Weapon (Colorless): 2% drop rate Nothing: 70% encounters
TIER 2 WOLF BEAST DROPS:
Chaos Crystal (White): 35% drop rate Chaos Crystal (Green): 10% drop rate Claw Weapon (White): 8% drop rate Claw Weapon (Green): 3% drop rate Fur Armor (White): 7% drop rate Fur Armor (Green): 2% drop rate Fang Component (White): 5% drop rate Nothing: 30% encounters
Lin Feng calculated expected equipment acquisition rates for a six-hour operation:
ESTIMATED ENCOUNTER RATES (6 HOURS, CONSERVATIVE HUNTING):
Tier 1 Rabbits: 8-12 encounters Tier 1 Scorpions: 3-5 encounters Tier 2 Wolves: 1-2 pack encounters (3-10 individual wolves)
EXPECTED DROPS (STATISTICAL AVERAGE):
Colorless Chaos Crystals: 2-3 White Chaos Crystals: 1-2 Green Chaos Crystals: 0-1 Colorless Components: 0-1 White Components: 0-2 Green Components: 0-1
The numbers confirmed what he'd suspected: equipment drops were uncommon enough that every piece mattered. The team couldn't afford to be wasteful or miss opportunities.
He programmed drop probability calculations into the Analysis Protocol so the system could recommend priority targets when multiple threats appeared simultaneously.
DROP TABLE ANALYSIS COMPLETE
PROBABILITY CALCULATIONS: INTEGRATED
TARGET PRIORITY RECOMMENDATIONS: ENABLED
Thursday, Lin Feng focused on team-specific training.
The team gathered in VR Training Hall C for specialized practice sessions designed around Green Valley threats.
"Today we train specifically for the beasts we'll face Saturday," Lin Feng announced as they entered their pods. "No random scenarios—targeted practice only."
The first simulation loaded: Eastern Forest environment with Tier 1 Rabbit Beasts.
"Chen Hao, you're primary interceptor," Lin Feng directed. "Rabbits lunge directly at targets. Use shield deflection at 30-degree angles to redirect momentum, then counter-attack during their 1.2-second recovery period."
Chen Hao practiced the technique repeatedly. Initial attempts were sloppy—wrong deflection angles that absorbed full impact instead of redirecting. But after twenty repetitions, he found the rhythm. Deflect, redirect, counter. Energy-efficient and effective.
"Good. Tang Yue, watch Chen Hao's energy consumption. Rabbit lunges hit hard—he'll need periodic support."
They ran through twelve Rabbit Beast encounters, refining their tactics with each iteration. Wang Min practiced harassment techniques—fast strikes to draw aggression, then retreat before the lunge. Li Xin worked on optimal counter-attack positioning—where to strike for maximum damage during the recovery window.
RABBIT BEAST TRAINING - 12 ENCOUNTERS
TEAM SUCCESS RATE: 100%
AVERAGE ENERGY CONSUMPTION: 68 UNITS PER ENCOUNTER
CHEN HAO INTERCEPT SUCCESS: 91%
The second simulation introduced Scorpion Beasts on rocky terrain.
"These are ranged enemies," Lin Feng explained. "The key is dodge timing and approach vectors. Wang Min, you're best suited for this—use your speed to close distance during reload windows."
Wang Min practiced dodging stinger projectiles. The Analysis Protocol provided precise timing calls: "Stinger fired. Dodge in 1.4 seconds... now!"
After fifteen practice runs, Wang Min's dodge success rate climbed to 94%. She learned to read the scorpion's attack telegraph—the tail curl preceding each shot gave 0.3 seconds warning.
Li Xin practiced the approach and elimination phase. Once in close range, he attacked the segment joints where exoskeleton armor was weakest. Piercing strikes proved far more effective than slashing attacks.
SCORPION BEAST TRAINING - 15 ENCOUNTERS
TEAM SUCCESS RATE: 100%
WANG MIN DODGE SUCCESS: 94%
LI XIN CLOSE COMBAT EFFICIENCY: 89%
POISON INCIDENTS: 2 (SUCCESSFULLY TREATED BY TANG YUE)
The third simulation was most challenging: Wolf pack encounters.
"Pack coordination is their strength," Lin Feng said. "We counter with our own coordination. Primary objective: identify and eliminate the alpha quickly. Secondary: prevent flanking."
The first wolf pack attempt went poorly. The team failed to identify the alpha fast enough, and the wolves executed perfect pincer formation. Chen Hao was overwhelmed by simultaneous attacks from three directions.
"Reset. I've programmed alpha identification markers into the system. Watch for these cues: larger size, central position, howl commands, other wolves deferring to its positioning."
The second attempt was better. Lin Feng's Analysis Protocol flagged the alpha within five seconds of engagement. The team focused fire—all three attackers concentrating on the alpha while Chen Hao blocked beta harassment and Tang Yue maintained energy support.
Alpha eliminated in eighteen seconds. The beta wolves' coordination immediately degraded, making them manageable individual threats.
They practiced wolf pack tactics for two hours, running through eight different scenarios with varying pack sizes and terrain.
WOLF PACK TRAINING - 8 ENCOUNTERS
SUCCESS RATE: 87.5% (1 FAILURE DUE TO DELAYED ALPHA IDENTIFICATION)
AVERAGE TIME TO ELIMINATE ALPHA: 16 SECONDS
PACK COORDINATION DISRUPTION: EFFECTIVE IN 7/7 SUCCESSFUL ENCOUNTERS
TEAM ENERGY CONSUMPTION: HIGH (180 UNITS AVERAGE PER PACK)
By the end of Thursday's training session, the team had practiced specific tactics for every common Green Valley threat. The improvement was measurable.
"Tomorrow we do one final comprehensive simulation," Lin Feng said as they exited the pods. "Mixed encounters, Green Valley terrain, six-hour duration. Treat it exactly like the real operation."
Friday brought the final preparation session.
The comprehensive simulation began at 2 PM. The VR system generated a perfect replica of Green Valley Zone—accurate terrain, realistic beast behavior based on Lin Feng's programmed models, authentic environmental conditions including the 1.1g gravity and dense atmosphere.
"Six-hour operation starts now," Instructor Zhao announced. "This is your final test before tomorrow's real entry. Treat it seriously."
The simulation was exhausting. They fought through Eastern Forest, engaged Scorpions on rocky outcrops, survived two Wolf pack encounters in Southern Grassland. The Analysis Protocol performed exactly as programmed, providing accurate tactical recommendations based on beast type and terrain.
SIX-HOUR COMPREHENSIVE SIMULATION - RESULTS:
ENCOUNTERS:
Tier 1 Rabbits: 11 (all successful) Tier 1 Scorpions: 4 (all successful) Tier 2 Wolf Packs: 2 (both successful)
EQUIPMENT DROPS (SIMULATED):
Colorless Crystals: 3 White Crystals: 2 White Component: 1
TEAM PERFORMANCE:
Zero casualties Average energy efficiency: 86% Coordination rating: Excellent Tactical decision quality: Outstanding
FINAL TEAM ENERGY LEVELS:
Lin Feng: 62% Chen Hao: 71% Tang Yue: 58% Li Xin: 64% Wang Min: 69%
"Outstanding work," Instructor Zhao said after they exited the simulation. "That performance demonstrates you're ready for real Green Valley operations. Your preparation is thorough, your coordination is solid, and your tactical discipline is excellent."
The team gathered outside the VR hall, tired but confident.
"We're ready," Li Xin said. "More ready than any first-year team has a right to be."
"The preparation was necessary," Lin Feng said. "Tomorrow isn't a simulation. We needed to train specifically for the actual threats we'll face."
"Do you think the real beasts will behave like your programmed models?" Wang Min asked.
"Probably 75-85% correlation," Lin Feng estimated. "The models are based on observational data from thousands of encounters. They're accurate generalizations, but individual beast behavior will have variance. That's why the Analysis Protocol includes adaptive algorithms—it will adjust recommendations based on actual behavior as we gather real data."
"I feel confident," Chen Hao said. "The deflection technique for Rabbit lunges feels natural now. I've practiced it so many times."
"Tang Yue, how are you feeling about energy management in extended operations?" Lin Feng asked.
"Comfortable. The six-hour simulation proved I can maintain support for that duration while keeping appropriate reserves. The poison treatment protocols are clear in my mind."
"Wang Min?"
"Less nervous than I was. The dodge timing for Scorpions is muscle memory now. And knowing exactly when to commit attacks instead of hesitating—that helps."
Lin Feng nodded. "Good. Everyone go rest tonight. Light dinner, early sleep, no late-night studying. Mental preparation is as important as tactical preparation. We meet at the portal facility at 7:15 AM tomorrow."
They dispersed to their dorms. Lin Feng returned to Room 314, where Chen Hao immediately collapsed onto his bed.
"I'm exhausted," Chen Hao groaned. "Six hours of combat simulation is brutal."
"Tomorrow will be more brutal," Lin Feng said. "Real combat has psychological stress that simulation can't replicate."
"Encouraging words, roommate."
"Realistic words. But we're prepared. The Analysis Protocol is ready, the team is trained, and we understand the threats."
That evening, Lin Feng entered his soul space one final time before the operation.
ANALYSIS PROTOCOL v0.3 - FINAL PRE-OPERATION STATUS
BEAST BEHAVIORAL DATABASE: COMPLETE (3 TYPES, 288 PROTOCOLS)
TERRAIN DATABASE: COMPLETE (47 ENVIRONMENTAL FACTORS)
DROP TABLE ANALYSIS: INTEGRATED
TEAM COORDINATION: OPTIMIZED FOR GREEN VALLEY
EMERGENCY PROTOCOLS: ACTIVE
SYSTEM OVERHEAD: 60 UNITS
ESTIMATED REAL-WORLD ACCURACY: 75-85%
STATUS: READY FOR OPERATION
He reviewed the preparation checklist one final time:
✓ Beast behavior thoroughly studied
✓ Terrain analysis complete
✓ Drop tables analyzed
✓ Tactical models programmed
✓ Team trained on specific threats
✓ Equipment verified
✓ Emergency protocols established
✓ Six-hour comprehensive simulation passed
Everything that could be prepared had been prepared.
Tomorrow, they would face the Land of Origin for real.
And Lin Feng had done everything in his power to ensure they would survive it.
STATUS: PREPARATION PHASE COMPLETE. GREEN VALLEY ZONE KNOWLEDGE COMPREHENSIVE. ANALYSIS PROTOCOL OPTIMIZED FOR KNOWN THREATS. TEAM READY FOR FIRST REAL OPERATION. SATURDAY 0800 HOURS: PORTAL ENTRY.
Lin Feng returned to the physical world, set his alarm, and prepared for sleep.
One more night of rest.
Then the real test began.