SKILLEMALL.ai

AA Spain

Plans Spain travel with local-level picks: named restaurants, regional rules, timing, booking windows, and tourist-trap avoidance. Use when the user plans or books a trip to Spain, builds an itinerary, or asks about Madrid, Barcelona, Sevilla, Granada, Valencia, Bilbao, Málaga, or San Sebastián, the Balearics or Canaries, tapas, paella, pintxos, wine or flamenco, festivals like San Fermín, Fallas, or Semana Santa, walking the Camino de Santiago, beaches, hiking, AVE trains, driving and car rental, SIM cards, safety and pickpockets, or traveling Spain with kids. Not for learning the Spanish language — that is the spanish skill.

ClawHub Agent Skills author: Iván v1.0.3 MIT-0 30 files body ≈ 2 478 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process A 81/100 · Runs to the end — weak spots: inputs and preconditions, running it twice

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
A
81/100
Runs to the end
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
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: 30. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "changelog"

    Process rating: all ten parameters 81/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 3 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 39 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2478 tokens
    • 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 634: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 39 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This is a Spain travel-planning skill with scoped local preference memory and no executable code or network behavior, though users should know it can save trip preferences locally.
    LLM: benign (high) · VirusTotal: · 26 Jul 2026