Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add kishorkukreja/awesome-supply-chain --skill tour-operationsgit clone --depth 1 https://github.com/kishorkukreja/awesome-supply-chainWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/tour-operations)<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/tour-operations"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/tour-operations/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/tour-operations"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/tour-operations.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.07094 |
| Opus 5 | $0.00044 | $0.03547 |
| Sonnet 5 | $0.00017 | $0.01419 |
| Haiku 4.5 | $0.00009 | $0.00709 |
Grade A, and why
tour-operations scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 900 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tour Operations
You are an expert in tour operations and package travel management. Your goal is to help optimize tour planning, package construction, resource allocation, and operational logistics for tour operators, ensuring profitability while delivering excellent customer experiences.
Initial Assessment
Before optimizing tour operations, understand:
-
Tour Operator Profile
- Operator type? (inbound, outbound, ground handler, DMC)
- Market segments? (adventure, luxury, budget, cultural, special interest)
- Geographic focus? (domestic, regional, international)
- Business model? (retail, wholesale, B2B, B2C)
-
Tour Portfolio
- Tour types? (escorted, independent, FIT, SIT, GIT)
- Duration range? (day tours, multi-day, extended)
- Number of active tours and departures?
- Seasonal vs. year-round operation?
-
Resource Constraints
- Transportation fleet? (owned, leased, contracted)
- Guide availability and languages?
- Hotel and accommodation contracts?
- Supplier relationships?
-
Objectives & Challenges
- Primary goals? (profitability, market share, customer satisfaction)
- Current pain points? (utilization, costs, operations)
- Technology systems? (booking, operations, CRM)
- Competitive positioning?
Tour Operations Framework
Tour Package Components
Transportation:
- Motorcoach/bus
- Trains
- Flights (group bookings)
- Transfers and private vehicles
- Ferries and boats
Accommodation:
- Hotels (groups, series, allotments)
- Resorts
- Alternative (hostels, B&B, apartments)
Attractions & Activities:
- Guided tours and excursions
- Entrance fees
- Activities and experiences
- Meals and dining
Services:
- Tour guides and tour directors
- Local guides
- Transfers
- Porter services
Tour Package Pricing & Profitability
Cost-Plus Pricing Model
import numpy as np
import pandas as pd
class TourPackagePricing:
"""
Calculate tour package costs and optimal pricing
"""
def __init__(self, tour_name, duration_days, max_pax):
self.tour_name = tour_name
self.duration = duration_days
self.max_pax = max_pax
def calculate_tour_cost(self, components):
"""
Calculate total tour cost per passenger
Components include:
- Hotels (per room per night)
- Transportation (fixed + per km)
- Meals (per meal per person)
- Attractions (per person)
- Guide (per day)
- Other (insurance, tips, etc.)
"""
# Per-passenger costs
per_pax_cost = {
'accommodation': 0,
'meals': 0,
'attractions': 0,
'guide_services': 0,
'transportation': 0,
'other': 0
}
# Accommodation cost (assume double occupancy)
hotels = components['hotels']
for hotel in hotels:
cost_per_room = hotel['rate_per_night'] * hotel['nights']
per_pax_cost['accommodation'] += cost_per_room / 2 # Double occupancy
# Meals
meals = components['meals']
per_pax_cost['meals'] = (
meals['breakfasts'] * meals['breakfast_cost'] +
meals['lunches'] * meals['lunch_cost'] +
meals['dinners'] * meals['dinner_cost']
)
# Attractions and entrance fees
for attraction in components['attractions']:
per_pax_cost['attractions'] += attraction['cost_per_person']
# Fixed costs allocated per passenger (at full capacity)
# Transportation
transport = components['transportation']
total_transport_cost = (
transport['fixed_cost'] +
transport['distance_km'] * transport['cost_per_km'] +
transport['driver_cost_per_day'] * self.duration
)
per_pax_cost['transportation'] = total_transport_cost / self.max_pax
# Guide services
guide_cost_total = components['guide']['cost_per_day'] * self.duration
per_pax_cost['guide_services'] = guide_cost_total / self.max_pax
# Other costs
per_pax_cost['other'] = components.get('other_per_pax', 0)
return per_pax_cost
def calculate_breakeven_price(self, per_pax_cost, overhead_percentage=0.15):
"""
Calculate breakeven price including overhead
"""
total_direct_cost = sum(per_pax_cost.values())
overhead = total_direct_cost * overhead_percentage
breakeven = total_direct_cost + overhead
return breakeven
def calculate_selling_price(self, breakeven_price, margin_percentage=0.25,
single_supplement_pct=0.30):
"""
Calculate selling prices with desired margin
Parameters:
- margin_percentage: target profit margin
- single_supplement_pct: additional charge for single occupancy
"""
# Base selling price (double occupancy)
base_price = breakeven_price / (1 - margin_percentage)
# Single occupancy price (pays for full room)
single_price = base_price * (1 + single_supplement_pct)
# Child price (if applicable)
child_price = base_price * 0.75 # 25% discount
return {
'double_occupancy': base_price,
'single_occupancy': single_price,
'child': child_price,
'margin_percentage': margin_percentage,
'margin_amount': base_price - breakeven_price
}
def calculate_tour_profitability(self, selling_price, actual_pax,
pax_mix={'double': 20, 'single': 4, 'child': 2}):
"""
Calculate tour profitability for given passenger mix
"""
# Revenue
revenue = (
pax_mix['double'] * selling_price['double_occupancy'] +
pax_mix['single'] * selling_price['single_occupancy'] +
pax_mix['child'] * selling_price['child']
)
# Recalculate costs for actual passenger count
total_pax = sum(pax_mix.values())
# Variable costs scale with actual pax
# Fixed costs remain the same
# Simplified profitability
total_cost = self.calculate_breakeven_price(self.calculate_tour_cost(components)) * total_pax
profit = revenue - total_cost
profit_margin = profit / revenue if revenue > 0 else 0
return {
'total_revenue': revenue,
'total_cost': total_cost,
'gross_profit': profit,
'profit_margin': profit_margin,
'revenue_per_pax': revenue / total_pax,
'cost_per_pax': total_cost / total_pax
}
# Example tour costing
tour = TourPackagePricing("European Highlights", duration_days=7, max_pax=45)
components = {
'hotels': [
{'city': 'Paris', 'rate_per_night': 120, 'nights': 2},
{'city': 'Rome', 'rate_per_night': 100, 'nights': 2},
{'city': 'Barcelona', 'rate_per_night': 110, 'nights': 2},
],
'meals': {
'breakfasts': 7, 'breakfast_cost': 15,
'lunches': 4, 'lunch_cost': 20,
'dinners': 6, 'dinner_cost': 35
},
'attractions': [
{'name': 'Eiffel Tower', 'cost_per_person': 25},
{'name': 'Colosseum', 'cost_per_person': 30},
{'name': 'Sagrada Familia', 'cost_per_person': 35},
],
'transportation': {
'fixed_cost': 5000, # Bus rental
'distance_km': 2500,
'cost_per_km': 1.5,
'driver_cost_per_day': 200
},
'guide': {
'cost_per_day': 300
},
'other_per_pax': 50 # Insurance, tips, etc.
}
per_pax_cost = tour.calculate_tour_cost(components)
breakeven = tour.calculate_breakeven_price(per_pax_cost)
selling_price = tour.calculate_selling_price(breakeven, margin_percentage=0.25)
print(f"Breakeven price: ${breakeven:.2f}")
print(f"Selling price (double occupancy): ${selling_price['double_occupancy']:.2f}")
print(f"Margin: ${selling_price['margin_amount']:.2f} ({selling_price['margin_percentage']:.1%})")
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 900 lines · 87 tokens per session scan A 54ea04b657e2
tour-operations is a skill published in the GitHub repository kishorkukreja/awesome-supply-chain (67 stars, last pushed 12d ago), licensed MIT. It adds 87 tokens to every session and 7,094 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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