SKILL Skill
description: Use when planning flights, comparing ticket prices, or asking about flight costs, airline fees, travel dates, or route options. Triggers on booking flights, cheap tickets, flight search, vé máy bay, săn vé rẻ, tối ưu chi phí bay, đặt vé, virtual interlining, or any flight-related cost question.
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Why use this skill
SKILL is most useful when you want an agent workflow that is more structured than an ad-hoc prompt. Instead of restating the same expectations every time, a dedicated SKILL.md file gives the assistant a repeatable brief. In this case, the core value is clarity: the repo already frames the workflow around frontend skills tasks, and the skill source gives you a portable starting point you can evaluate, adapt, and reuse. The inferred platform for this skill is Generic Skills, which helps you judge whether it is likely to feel native in your current agent ecosystem or whether it is better treated as a general reference.
That matters because AI assistants are better when the operating context is explicit. A good skill turns hidden team expectations into visible instructions. It can name preferred tools, describe failure modes, define what “done” looks like, and reduce the amount of corrective prompting you need after the first draft. For developers exploring the wider SKILL.md ecosystem, this page helps answer the practical question: is this skill specific and maintained enough to be worth trying?
How to evaluate and use it
Start with the source repo and the preview below. The preview tells you whether the instructions are actionable or just aspirational. Strong skills usually describe triggers, recommended tools, steps, and known pitfalls. Weak skills tend to stay generic. This one lives in dotanminh/travel-optimization-engine, which gives you a concrete repo context, update history, and direct ownership trail.
Once you confirm the scope looks right, test it on a small task before making it part of a larger workflow. If it improves consistency, keep it. If it is too broad, outdated, or conflicts with your own process, treat it as a reference rather than a drop-in rule. That is the healthiest way to use directory-discovered skills: not as magic plugins, but as reusable operational knowledge that still deserves judgment.
SKILL.md preview
Previewing the source is one of the fastest ways to judge whether a skill is truly useful. This snippet comes from the public file in the linked repository.
--- name: travel-optimization-engine description: Use when planning flights, comparing ticket prices, or asking about flight costs, airline fees, travel dates, or route options. Triggers on booking flights, cheap tickets, flight search, vé máy bay, săn vé rẻ, tối ưu chi phí bay, đặt vé, virtual interlining, or any flight-related cost question. --- # Travel Optimization Engine A decision support system for flight ticket cost optimization. Coordinates 8 specialized skills to analyze every angle of flight pricing before you book. ## Setup API keys required as environment variables (optional — skills work in AI-knowledge mode without APIs): - `AMADEUS_API_KEY` + `AMADEUS_API_SECRET` — register at developers.amadeus.com - `KIWI_API_KEY` — register at tequila.kiwi.com/portal Shared API clients: `scripts/amadeus_client.py`, `scripts/kiwi_client.py`, `scripts/normalize.py` ## Phase 1: Collect Traveler Profile Before running any analysis, gather this profile (ask only what's missing). See `references/user-profile-schema.md` for full schema. ``` REQUIRED: - origin: IATA code or city name (e.g., HAN, "Hanoi") - destination: IATA code or city name (e.g., SFO, "San Francisco") - departure_date: target date or range - passengers: number + types (adult/child/infant) OPTIONAL (improves accuracy): - return_date: one-way if empty - flexibility: low (±2 days) | medium (±7 days) | high (±14 days) - baggage: carry_on | checked_1 | checked_2 - booking_type: personal | corporate - loyalty_programs: airline codes (e.g., VN, QR) - risk_tolerance: conservative | moderate | aggressive - cabi ...