SKILLEMALL.ai

AC travel-itinerary-builder

Comprehensive travel itinerary generator that creates detailed, multi-day trip plans with automatic weather forecasts, points of interest, restaurant recommendations, transportation logistics, and budget estimates. Generates print-ready HTML documents with dark theme styling. Use when: (1) Planning a trip and need a complete itinerary, (2) User provides destination(s) and dates, (3) Organizing travel bookings (flights, hotels, car rentals) from Gmail, (4) Need multi-language support for destination names, (5) Creating printable travel documents, (6) Estimating travel budgets and costs.

ClawHub Agent Skills author: rachelchoo1212 v1.0.2 9 files body ≈ 2 483 tokens Open the sourceclawhub.ai analyzed 3 d ago

Comprehensive travel itinerary generator that creates detailed, multi-day trip plans with automatic weather forecasts, points of interest, restaurant…

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

GeneratorGmailNotionData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 9. 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 62/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 105 steps, 2 vague phrases
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2483 tokens
    • 100Running it twice. No mutating operations
    • low 13 top-level sections: this looks like several domains in one skill

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -214 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 592: enough signal without eating the budget
    • +4Structure: 34 headings
    • +3Step-by-step instructions: 105 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: suspicious
    The skill fits a travel-planning purpose, but it handles Gmail booking data and credentials with weak containment and can generate unsafe HTML from unescaped travel data.
    LLM: suspicious (high) · VirusTotal: · 11 Sept 2026