AB moodtrip-hotel-search
Search, compare, evaluate, and hand off hotel bookings using the MoodTrip.ai MCP server (api.moodtrip.ai). Use this skill whenever the user mentions hotels, accommodation, lodging, stays, travel bookings, hotel search, hotel comparison, hotel reviews, hotel pricing, or anything related to finding or booking a place to stay. Also trigger when the user asks about hotel amenities, room types, check-in/check-out logistics, travel destinations with accommodation needs, or says things like "find me a hotel", "where should I stay", "book a room", "hotel recommendations", or "compare hotels". This skill connects to the MoodTrip MCP server which provides real-time hotel inventory, pricing, semantic search, reviews, and booking link handoff via LiteAPI.
As a process B 66/100 · Nearly there — weak spots: result and completion, inputs and preconditions
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 66/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 85Steps. 22 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 8 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2199 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 753: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 22 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.