SR22T Runway Brief Skill

⚠️ CRITICAL: MANDATORY DATA USAGE - READ FIRST

SAFETY-CRITICAL REQUIREMENT: This skill contains actual Cirrus SR22T POH performance data. Using incorrect data could result in runway overruns, accidents, or fatalities.

BEFORE Writing ANY Code:

STEP 1: Read the reference files FIRST

cat references/sr22t_performance_data.py
cat references/calculation_functions.py

STEP 2: Import and use ONLY the provided data

import sys
sys.path.insert(0, 'references')
from sr22t_performance_data import EMBEDDED_SR22T_PERFORMANCE
from calculation_functions import (
    calculate_pressure_altitude,
    calculate_isa_temperature,
    calculate_density_altitude,
    calculate_wind_components,
    interpolate_performance
)

STEP 3: Extract performance tables - DO NOT create your own

takeoff_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["takeoff_distance"]["conditions"]
landing_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["landing_distance"]["conditions"]
v_speeds = EMBEDDED_SR22T_PERFORMANCE["v_speeds"]["approach_speeds"]

❌ PROHIBITED:

• NEVER create performance data from memory
• NEVER simplify or approximate POH tables
• NEVER skip reading the reference files
• NEVER use simple linear interpolation (must be bilinear on PA AND temperature)

✅ VALIDATION:

• Used data from EMBEDDED_SR22T_PERFORMANCE
• Used bilinear interpolation on PA AND temperature
• Rounded to nearest 50 ft
• Results are conservative

If you cannot access the reference files, STOP and inform the user. Do not proceed with estimated data.

---

Required Inputs

1. Runway elevation (ft MSL), 2. Temperature (°C), 3. Altimeter (inHg), 4. Wind direction (°mag), 5. Wind speed (kt), 6. Runway heading (°mag), 7. Runway length (ft)

Optional: Wind gusts, Operation type (takeoff/landing/both)

---

Workflow

Step 0: Determine Operation Type

CRITICAL: The skill MUST analyze the user's request to determine operation type.

Automatic Detection (Priority 1): Scan the user's request for explicit keywords:

• Takeoff only: "departing", "takeoff", "departure", "leaving from"
• Landing only: "arriving", "landing", "arrival", "coming into"
• Both operations: If NEITHER takeoff NOR landing keywords detected, OR if BOTH detected

Examples:

• "I'm departing KBZN runway 30" → Takeoff brief only
• "Give me a landing brief for KSUN runway 09" → Landing brief only
• "Analyze KBZN runway 30" → Both operations (no specific operation mentioned)
• "I need performance data for KASE runway 15" → Both operations (ambiguous)

Default Behavior:

• If ambiguous or unspecified → ALWAYS calculate BOTH operations
• Never ask the user to clarify operation type
• If in doubt, do both - it's better to provide complete information

Set Operation Mode:

# Detect from user input
if "depart" in user_input.lower() or "takeoff" in user_input.lower():
    operation = "takeoff"
elif "arriv" in user_input.lower() or "landing" in user_input.lower():
    operation = "landing"
else:
    operation = "both"  # DEFAULT: Do both when ambiguous

Proceed with selected workflows based on detected operation type.

---

Step 1: Gather and Validate Inputs

Automatic Airport Data Lookup: If the user provides an airport code but is missing elevation or runway length:

1. Use web_search to find airport data
2. Query format: "[AIRPORT_CODE] airport elevation runways"
3. Extract from authoritative sources (Wikipedia, airnav.com, skyvector.com, airport-data.com)
4. Data to retrieve:
   • Field elevation (use for all runways - runway-specific elevation differences are negligible for performance)
   • All runway identifications and lengths
5. If multiple sources differ on runway length, use the most conservative (shortest) length
6. If search fails or returns unclear results: prompt user for missing data

Do not let web search failure block the briefing - simply request the missing data from the user.

Never assume or estimate critical data - always get confirmed elevation and runway lengths.

Prompt format:

RUNWAY INFORMATION:
- Runway ID: [e.g., "09"]
- Airport Code: [e.g., "KBZN"] (optional, enables automatic lookup)
- Airport Name: [e.g., "Sun Valley"] (optional)
- Elevation: [feet MSL] (will search if not provided)
- Runway Heading: [degrees magnetic]
- Runway Length: [feet] (will search if not provided)

CURRENT WEATHER:
- Temperature: [°C]
- Altimeter: [inHg]
- Wind Direction: [degrees magnetic]
- Wind Speed: [knots]
- Wind Gusts: [knots or "none"]

Validation:

• Elevation: 0-14,000 ft (warn if >14,000)
• Temperature: -40 to +50°C (confirm if unusual)
• Altimeter: 28.00-31.00 inHg (warn if outside)
• Headings: 0-360°
• Wind speed: 0-60 kt (flag if >30 kt)
• Runway length: 1,000-15,000 ft (flag if <2,000 ft)

If validation fails, request correction before proceeding.

---

Step 2: Calculate Common Performance Data

Execute using Python code in references/calculation_functions.py:

Pressure Altitude:

pressure_altitude = field_elevation + (29.92 - altimeter) * 1000
pressure_altitude_rounded = round(pressure_altitude / 10) * 10

ISA Temperature:

isa_temp = 15 - (2 * (pressure_altitude / 1000))

Density Altitude:

density_altitude = pressure_altitude + (120 * (actual_temp - isa_temp))
density_altitude_rounded = round(density_altitude / 50) * 50

Wind Components:

# Use the imported function - DO NOT rewrite this calculation
# Signature: calculate_wind_components(wind_dir_mag, wind_speed_kt, runway_heading_mag)
wind_result = calculate_wind_components(wind_direction, wind_speed, runway_heading)

headwind = wind_result["headwind_kt"]  # Positive = headwind, Negative = tailwind
crosswind = wind_result["crosswind_kt"]  # Always positive
wind_type = wind_result["wind_type"]  # "headwind" or "tailwind"

Density Altitude Impact Assessment:

• <2,000 ft: "Excellent performance"
• 2,000-5,000 ft: "Good performance, minor reduction"
• 5,000-8,000 ft: "Noticeable performance reduction"
• 8,000-10,000 ft: "Significant reduction - caution"

• 10,000 ft: "Severe degradation - high risk"

Display summary before proceeding to operations.

---

Step 3A: Takeoff Brief (if selected)

3A.1: Interpolate Takeoff Distance

Use the imported interpolate_performance() function - DO NOT rewrite this:

# Get takeoff data
takeoff_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["takeoff_distance"]["conditions"]

# Use the interpolate_performance function (handles bilinear interpolation automatically)
takeoff_result = interpolate_performance(
    takeoff_data,
    pressure_altitude,
    actual_temp,
    ['ground_roll_ft', 'total_distance_ft']
)

takeoff_ground_roll = takeoff_result['ground_roll_ft']  # Already rounded to nearest 50 ft
takeoff_total_distance = takeoff_result['total_distance_ft']  # Already rounded
takeoff_margin = runway_length - takeoff_total_distance

3A.2: Calculate Climb Gradients

Use the imported interpolate_performance() function - DO NOT rewrite this:

# Get climb gradient data
climb_91_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["takeoff_climb_gradient_91"]["conditions"]
climb_120_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["enroute_climb_gradient_120"]["conditions"]

# Use interpolate_performance (handles bilinear interpolation and rounding automatically)
# Note: Pass None for value_keys because climb gradient data has values at root level
gradient_91 = interpolate_performance(climb_91_data, pressure_altitude, actual_temp, None)  # ft/NM
gradient_120 = interpolate_performance(climb_120_data, pressure_altitude, actual_temp, None)  # ft/NM

# Already rounded to nearest 10 ft/NM by the function

3A.3: Calculate CAPS Altitudes

caps_minimum_msl = runway_elevation + 600  # 600 ft AGL minimum
caps_recommended_msl = runway_elevation + 2000  # 2000 ft AGL optimal
pattern_altitude_msl = runway_elevation + 1000  # Standard pattern

3A.4: Generate Departure Passenger Brief

MANDATORY SAFETY ITEMS (Must ALWAYS be included):

1. Sterile Cockpit - No talking during takeoff/landing/ATC; tap shoulder if urgent
2. CAPS Parachute - Red handle location, only pilot touches unless incapacitated
3. Fire Extinguisher - Located by pilot's left leg
4. Emergency Egress Hammer - Located under center console
5. Air Sickness Bags - In seatback pockets
6. TKS Anti-Ice - Plane is equipped (mention if icing visible, no alarm needed)

Additional contextual tidbits encouraged - Weather, winds, interesting facts, jokes, etc.

# Determine weather tone based on density altitude
if density_altitude < 5000:
    weather_tone = "excellent conditions for takeoff"
    performance_note = "We'll have a nice brisk climb out."
elif density_altitude < 8000:
    weather_tone = "good conditions, though you'll notice a longer takeoff roll at this elevation"
    performance_note = "The takeoff will be a bit longer than sea level—completely normal."
elif density_altitude < 10000:
    weather_tone = "high elevation and warm temperatures, so we'll have an extended takeoff roll"
    performance_note = "We'll use more runway and have a gradual climb—standard for mountain flying."
else:
    weather_tone = "very high density altitude today"
    performance_note = "Expect an extended takeoff roll and gradual climb—this is normal at high elevations in warm weather."

# Add wind mention if significant
if abs(headwind) > 10:
    wind_mention = f"We have a {int(abs(headwind))}-knot {'headwind helping us out' if wind_type == 'headwind' else 'tailwind to account for'}. "
elif crosswind > 10:
    wind_mention = f"There's a {int(crosswind)}-knot crosswind today, so you might feel me working the controls a bit. "
else:
    wind_mention = ""

# MANDATORY safety briefing structure
safety_items = f"""
**Today's Flight:**

{wind_mention}{performance_note} {weather_tone.capitalize()}. Keep your seatbelt snug during the climb, and feel free to ask questions once we're established in cruise flight.

---

**Safety Briefing:**

Before we depart, a quick safety overview:

**Sterile Cockpit:** During takeoff, landing, and when I'm talking to air traffic control, I need you to hold all non-urgent questions—if something is truly urgent, tap me on the shoulder.

**Emergency Equipment:**
- CAPS Parachute System: This Cirrus has a whole-airframe parachute system. The red handle is right here [indicate location between the seats]. This is for emergencies only—never touch it unless I'm incapacitated and we're in an unrecoverable situation. I'll handle it if needed.
- Fire extinguisher: By my left leg
- Emergency egress hammer: Under the center console (for breaking windows if needed)
- Air sickness bags: In the seatback pockets if you need them

**Weather Systems:** This plane is equipped with TKS anti-ice, so if you notice any fluid on the wings or see me activate it in flight, that's normal—no cause for alarm.
"""

# Optional: Add contextual tidbits (airport facts, scenic notes, weather trivia, etc.)
# Example: If high elevation airport, mention interesting facts about the location
# Example: If scenic departure, mention views to expect
# LLM should add 1-2 contextual notes based on conditions/location if appropriate

passenger_brief = safety_items.strip()

3A.5: Format Takeoff Brief Output

OUTPUT ORDER (CRITICAL):

1. GO/NO-GO Decision
2. Departure Passenger Brief
3. Emergency Brief
4. Safety Notes
5. Takeoff Performance
6. Additional Information

# SR22T TAKEOFF BRIEF - {Airport} Runway {ID}

## 1. GO/NO-GO DECISION
**{✅ GO / ⚠️ GO WITH CAUTION / ❌ NO-GO}**

{Decision reasoning with specific factors}

**Runway Margin:** {margin} ft ({percent}% - {EXCELLENT/GOOD/ADEQUATE/MARGINAL/INSUFFICIENT})

---

## 2. DEPARTURE PASSENGER BRIEF
{passenger_brief}

---

## 3. EMERGENCY BRIEF - Phased Approach

**Phase 1 (Ground Roll - 0 to rotation):**
If engine failure occurs before rotation: **ABORT TAKEOFF** - Close throttle, apply brakes, stop on remaining runway ({remaining} ft available).

**Phase 2 (Rotation to {caps_min} ft MSL):**
If engine failure: Land straight ahead or within 30° of runway heading. Insufficient altitude for CAPS deployment.

**Phase 3 ({caps_min} to {caps_rec} ft MSL):**
If engine failure: **IMMEDIATE CAPS DEPLOYMENT** - Pull red handle without hesitation. Limited time for successful deployment at these altitudes.

**Phase 4 (Above {caps_rec} ft MSL):**
If engine failure: Troubleshoot per POH checklist. CAPS available if unable to resolve. Time permits decision-making.

---

## 4. SAFETY NOTES
{context-specific warnings for high DA, crosswinds, gusts, tailwinds, terrain, etc.}

---

## 5. TAKEOFF PERFORMANCE

### Performance Summary
**Pressure Altitude:** {pa} ft
**Density Altitude:** {da} ft (ISA {+/-}X°C - {assessment})

**Wind Analysis:**
- {Headwind/Tailwind}: {component} kt
- Crosswind: {component} kt

### Takeoff Distances
**Ground Roll:** {distance} ft
**Total Distance to 50ft:** {distance} ft

**Runway Analysis:**
- Available: {length} ft
- Required: {total_distance} ft
- **Margin: {margin} ft ({percent}% - {EXCELLENT/GOOD/ADEQUATE/MARGINAL/INSUFFICIENT})**

### Climb Performance
**At 91 KIAS (Initial Climb):** {gradient} ft/NM
**At 120 KIAS (Enroute Climb):** {gradient} ft/NM

### CAPS Altitudes
**Field Elevation:** {elevation} ft MSL
**CAPS Minimum:** {alt} ft MSL (600 ft AGL) - Emergency deployment only
**CAPS Recommended:** {alt} ft MSL (2,000 ft AGL) - Optimal deployment window
**Pattern Altitude:** {alt} ft MSL (1,000 ft AGL) - CAPS fully effective

---

## 6. ADDITIONAL INFORMATION

**Weather Conditions:**
- Temperature: {temp}°C
- Altimeter: {alt} inHg
- Winds: {dir}°/{speed} kt{" gusting " + gusts if gusts else ""}

**Runway Details:**
- Runway: {id}
- Heading: {hdg}° magnetic
- Length: {length} ft

Margin Categories:

• EXCELLENT: >150%
• GOOD: 125-150%
• ADEQUATE: 110-125%
• MARGINAL: 100-110%
• INSUFFICIENT: <100% → NO-GO

---

Step 3B: Landing Brief (if selected)

3B.1: Determine Flap Configuration

SR22T ALWAYS uses 100% flaps for landing unless flaps are inoperative.

gust_factor = wind_gusts - wind_speed if wind_gusts else 0

# SR22T Standard: ALWAYS full flaps
flap_config = "full_flaps"
reason = "SR22T standard configuration (100% flaps)"

# Note crosswind/gust conditions but do NOT reduce flaps
if crosswind >= 15:
    technique_note = f"Strong crosswind ({int(crosswind)} kt) - use wing-low method, full aileron into wind"
elif crosswind >= 10:
    technique_note = f"Moderate crosswind ({int(crosswind)} kt) - maintain positive crosswind correction"
elif gust_factor >= 10:
    technique_note = f"Gusty conditions (+{int(gust_factor)} kt gusts) - maintain extra energy on final"
else:
    technique_note = "Normal wind conditions"

# Get speeds from v_speeds table (always full_flaps for SR22T)
v_speeds = EMBEDDED_SR22T_PERFORMANCE["v_speeds"]["approach_speeds"][flap_config]
base_final = v_speeds["final_approach_base_kias"]
threshold = v_speeds["threshold_crossing_kias"]
touchdown = v_speeds["touchdown_target_kias"]

3B.2: Apply Gust Corrections

gust_correction = round(gust_factor * 0.5, 1) if gust_factor > 0 else 0
final_approach_speed = round(base_final + gust_correction)

3B.3: Interpolate Landing Distance

Use the imported interpolate_performance() function - DO NOT rewrite this:

# Get landing data
landing_data = EMBEDDED_SR22T_PERFORMANCE["performance_data"]["landing_distance"]["conditions"]

# Use interpolate_performance (handles bilinear interpolation automatically)
landing_result = interpolate_performance(
    landing_data,
    pressure_altitude,
    actual_temp,
    ['ground_roll_ft', 'total_distance_ft']
)

landing_ground_roll = landing_result['ground_roll_ft']  # Already rounded to nearest 50 ft
landing_total_distance = landing_result['total_distance_ft']  # Already rounded
landing_margin = runway_length - landing_total_distance

3B.4: Generate Arrival Passenger Brief

if crosswind > 10 or gust_factor > 10:
    conditions = f"with {'gusty ' if gust_factor > 10 else ''}{'crosswinds' if crosswind > 10 else 'winds'}, so you might notice the nose pointed into the wind—completely normal"
elif density_altitude > 8000:
    conditions = "at a high-elevation airport with a slightly longer approach—normal for these conditions"
else:
    conditions = "with smooth conditions expected"

arrival_brief = f"We should be landing at {airport_name if provided else 'our destination'} in about twelve minutes. Temperature on the ground is {int(actual_temp)} degrees {conditions}. I'll need to focus on the approach, so I'll go quiet for a few minutes—make sure your seatbelt is snug and anything loose is secured."

3B.5: Format Landing Brief Output

OUTPUT ORDER (CRITICAL):

1. GO/NO-GO Decision
2. Arrival Passenger Brief
3. Go-Around Brief
4. Safety Notes
5. Landing Performance
6. Additional Information

# SR22T LANDING BRIEF - {Airport} Runway {ID}

## 1. GO/NO-GO DECISION
**{✅ GO / ⚠️ GO WITH CAUTION / ❌ NO-GO}**

{Decision reasoning with specific factors}

**Runway Margin:** {margin} ft ({percent}% - {EXCELLENT/GOOD/ADEQUATE/MARGINAL/INSUFFICIENT})

---

## 2. ARRIVAL PASSENGER BRIEF
{arrival_brief}

---

## 3. GO-AROUND BRIEF

**If go-around is required:**
- Full throttle immediately
- Positive rate of climb → Gear up
- Climb at Vy (best rate): 100 KIAS
- Expect reduced climb performance at density altitude {da} ft
- Estimated climb gradient: {gradient_120} ft/NM (from performance data)
- CAPS available above {caps_min} ft MSL if unable to climb

{Density altitude specific considerations}

---

## 4. SAFETY NOTES
{conditions-specific warnings for crosswinds, gusts, density altitude, tailwinds, short runway, etc.}

---

## 5. LANDING PERFORMANCE

### Performance Summary
**Pressure Altitude:** {pa} ft
**Density Altitude:** {da} ft (ISA {+/-}X°C)

**Wind Analysis:**
- {Headwind/Tailwind}: {component} kt
- Crosswind: {component} kt
{if gusts: - **Gusts:** +{factor} kt}

### Approach Configuration
**Configuration:** 100% Flaps (SR22T standard)
- Final Approach: {speed} KIAS ({base} + {correction} gust)
- Threshold: {speed} KIAS
- Touchdown Target: {speed} KIAS

**Technique Notes:** {technique_note}

### Landing Distances
**Ground Roll:** {distance} ft
**Total Distance:** {distance} ft

**Runway Analysis:**
- Available: {length} ft
- Required: {total} ft
- **Margin: {margin} ft ({percent}% - {assessment})**

### Wind Considerations
{Specific guidance for crosswind, gusts, headwind/tailwind}

---

## 6. ADDITIONAL INFORMATION

**Weather Conditions:**
- Temperature: {temp}°C
- Altimeter: {alt} inHg
- Winds: {dir}°/{speed} kt{" gusting " + gusts if gusts else ""}

**Runway Details:**
- Runway: {id}
- Heading: {hdg}° magnetic
- Length: {length} ft

---

Step 4: Combined Analysis (if both selected)

Generate both briefs, then add:

## COMPARATIVE ANALYSIS

**Runway Margins:**
- Takeoff: {margin} ft ({percent}%)
- Landing: {margin} ft ({percent}%)
- **Most Restrictive:** {takeoff/landing}

**Performance Considerations:**
{Analysis of which operation is limiting and why}

**Round-Trip Viability:**
{Assessment if both operations viable}

**OVERALL GO/NO-GO: {decision with combined reasoning}**

---

Validation Checklist

Before delivering brief, verify:

Calculations:

• Interpolations used correct bounding data
• Roundings applied (10 ft for PA, 50 ft for DA/distances)
• Wind components calculated correctly
• Margin = available - required (positive = safe)

Completeness:

• All sections present
• Passenger brief included
• Specific numbers (no placeholders)
• Assessment categories correct

Safety Logic:

• Margin <10% or negative → NO-GO
• Margin 10-25% → GO WITH CAUTION
• Margin >25% → GO (with advisories if needed)
• All warnings for high DA, crosswinds, gusts, tailwinds

---

Reference Files

Performance Data: references/sr22t_performance_data.py

• Complete takeoff/landing tables
• Climb gradient tables
• V-speeds with approach configurations

Calculation Functions: references/calculation_functions.py

• All formulas with test cases
• Interpolation algorithms
• Wind component calculations

V-Speeds Guide: references/v-speeds-reference.md

• Flap configuration selection logic
• Gust correction methodology
• Wind technique guidance

Examples: examples/

• High density altitude scenario
• Crosswind landing scenario
• Round-trip analysis

---

Usage Notes

For LLM:

1. Request inputs if not provided
2. Execute calculations using provided Python code
3. Use exact interpolation algorithms (don't approximate)
4. Apply validation checklist before delivering
5. Provide clear GO/NO-GO with specific reasoning

Adaptation:

• Adjust passenger brief tone for nervous flyers or children
• Flag marginal conditions proactively
• Suggest alternates if NO-GO
• Recommend waiting for better conditions if borderline

Consistency Critical: Same inputs must produce identical outputs across runs for safety.