Recreation Priority

Description

Prioritizes trail repairs using multi-factor analysis to optimize resource allocation and maximize public benefit. Evaluates trails based on usage patterns, access value, cost-effectiveness, and strategic importance to create a prioritized repair schedule. This is the Trail Assessor's primary tool for budget planning and repair sequencing.

Triggers

When should the agent invoke this skill?

•User asks about trail repair priorities or sequencing
•Query mentions budget allocation or resource planning
•Request for quick-win opportunities or low-hanging fruit
•Questions about trail ranking by importance
•Usage-based prioritization requests
•Cost-effectiveness analysis needed
•Multi-year repair planning discussions

Instructions

Step-by-step reasoning for the agent:

•
Load Trail Data: Retrieve trail and damage data for the specified fire
- •Accept fire_id parameter to identify the fire
- •Optionally apply budget constraint
- •Load from Cedar Creek fixtures or provided data
•
Calculate Usage Score (0-100): Evaluate visitor traffic and value
- •Priority rank from field assessment (inverse: rank 1 = highest)
- •Trail miles (longer = higher value)
- •Trail class (lower class = higher usage typically)
•
Calculate Access Score (0-100): Evaluate connectivity and alternatives
- •Wilderness gateway access
- •Connection to other trail systems
- •Unique destination value
- •Seasonal access window
•
Calculate Cost-Effectiveness (0-100): Balance cost vs. benefit
- •Repair cost per mile
- •Crew days required
- •Benefit-to-cost ratio
•
Identify Quick Wins: Low-cost, high-impact opportunities
- •Cost < $15,000
- •High usage score (>60)
- •Short timeline (<2 months)
•
Allocate Resources: If budget provided, optimize allocation
- •Sort by composite priority score
- •Fit trails within budget constraint
- •Identify budget shortfall and deferred trails
•Generate Reasoning Chain: Document prioritization decisions

Inputs

Input	Type	Required	Description
fire_id	string	Yes	Unique fire identifier (e.g., "cedar-creek-2022")
budget	number	No	Optional budget constraint in dollars (no limit if not provided)
include_quick_wins	boolean	No	Whether to identify quick-win opportunities (default: true)

Outputs

Output	Type	Description
fire_id	string	The analyzed fire identifier
total_trails	number	Number of trails analyzed
priority_ranking	array	Trails ranked by composite priority score
quick_wins	array	Low-cost, high-impact opportunities
resource_allocation	object	Budget allocation if budget provided
factor_scores	object	Usage, access, and cost scores per trail
reasoning_chain	array	Step-by-step prioritization decisions
confidence	number	Assessment confidence (0-1)
data_sources	array	Sources used
recommendations	array	Repair sequencing recommendations

Reasoning Chain

Step-by-step reasoning for the agent:

•First, identify the fire by ID and load trail damage data
•Then, calculate usage, access, and cost-effectiveness scores for each trail
•Next, compute composite priority score using weighted factors
•Then, identify quick-win opportunities based on cost and impact
•If budget provided, allocate resources optimally within constraints
•Finally, generate sequenced repair recommendations

Resources

•resources/priority-weights.json - Factor weights and quick-win thresholds

Scripts

•
scripts/prioritize_trails.py - Python implementation of trail prioritization
- •Function: execute(inputs: dict) -> dict
- •Inputs: {"fire_id": "cedar-creek-2022", "budget": 200000}
- •Returns: Complete prioritization with rankings and budget allocation

Examples

Example 1: Full Prioritization

Input:

json

{
  "fire_id": "cedar-creek-2022",
  "include_quick_wins": true
}

Output:

json

{
  "fire_id": "cedar-creek-2022",
  "total_trails": 5,
  "priority_ranking": [
    {
      "rank": 1,
      "trail_id": "waldo-lake-3536",
      "trail_name": "Waldo Lake Trail #3536",
      "priority_score": 87.5,
      "usage_score": 95.0,
      "access_score": 85.0,
      "cost_effectiveness": 65.0,
      "total_cost": 133500,
      "rationale": "Primary recreation access. High visitor use. Critical for 2024 season."
    },
    {
      "rank": 2,
      "trail_id": "hills-creek-3510",
      "trail_name": "Hills Creek Trail #3510",
      "priority_score": 82.0,
      "usage_score": 80.0,
      "access_score": 90.0,
      "cost_effectiveness": 45.0,
      "total_cost": 238000,
      "rationale": "Access route for timber salvage. Economic recovery value."
    }
  ],
  "quick_wins": [
    {
      "trail_id": "timpanogas-3527",
      "trail_name": "Timpanogas Lake Trail #3527",
      "total_cost": 4800,
      "priority_score": 68.0,
      "estimated_timeline": "1 month",
      "rationale": "Minimal damage. Low cost. Quick reopening opportunity."
    },
    {
      "trail_id": "charlton-lake-3578",
      "trail_name": "Charlton Lake Trail #3578",
      "total_cost": 10500,
      "priority_score": 72.0,
      "estimated_timeline": "1-2 months",
      "rationale": "Moderate use. Can reopen quickly with minimal investment."
    }
  ],
  "reasoning_chain": [
    "Evaluating 5 trails for Cedar Creek Fire",
    "Waldo Lake Trail: Usage 95.0, Access 85.0, Cost-Eff 65.0 -> Priority 87.5",
    "Hills Creek Trail: Usage 80.0, Access 90.0, Cost-Eff 45.0 -> Priority 82.0",
    "Identified 2 quick wins: Timpanogas ($4.8K), Charlton ($10.5K)"
  ],
  "confidence": 0.85,
  "data_sources": ["Cedar Creek field assessment 2022-10-25"],
  "recommendations": [
    "Phase 1: Address quick wins (Timpanogas, Charlton) for early reopenings",
    "Phase 2: Prioritize Waldo Lake Trail (primary access, high use)",
    "Phase 3: Coordinate Hills Creek Trail repair with timber salvage operations"
  ]
}

Example 2: Budget-Constrained Allocation

Input:

json

{
  "fire_id": "cedar-creek-2022",
  "budget": 200000
}

Output:

json

{
  "fire_id": "cedar-creek-2022",
  "total_trails": 5,
  "budget": 200000,
  "resource_allocation": {
    "funded_trails": [
      {
        "trail_id": "waldo-lake-3536",
        "trail_name": "Waldo Lake Trail #3536",
        "cost": 133500,
        "priority_score": 87.5
      },
      {
        "trail_id": "bobby-lake-3526",
        "trail_name": "Bobby Lake Trail #3526",
        "cost": 60000,
        "priority_score": 75.0
      }
    ],
    "total_allocated": 193500,
    "remaining_budget": 6500,
    "deferred_trails": [
      {
        "trail_id": "hills-creek-3510",
        "trail_name": "Hills Creek Trail #3510",
        "cost": 238000,
        "priority_score": 82.0,
        "shortfall": 231500
      }
    ]
  },
  "quick_wins": [
    {
      "trail_id": "timpanogas-3527",
      "total_cost": 4800,
      "status": "Can be funded with remaining budget"
    }
  ],
  "reasoning_chain": [
    "Budget: $200,000 available",
    "Rank 1: Waldo Lake ($133.5K) - Funded",
    "Rank 2: Bobby Lake ($60K) - Funded (Total: $193.5K)",
    "Rank 3: Hills Creek ($238K) - Deferred (exceeds budget)",
    "Quick win: Timpanogas ($4.8K) fits in remaining $6.5K"
  ],
  "recommendations": [
    "Fund Waldo Lake and Bobby Lake trails within $200K budget",
    "Use remaining $6.5K for Timpanogas quick win",
    "Seek additional $231.5K for Hills Creek Trail in next fiscal year"
  ]
}

References

•USFS Recreation Priority Framework
•Trail Repair Cost Estimation Guidelines
•Cedar Creek Trail Damage Fixture: data/fixtures/cedar-creek/trail-damage.json