SKILLEMALL.ai

BB Travel

Runs a traveler's standing system: dream list, passports and visas, Schengen day counts, bookings, points, budgets, and what broke last time. Use when someone names a destination they want to visit someday, when a passport, visa, ETA, or entry rule has to be checked before dates are fixed, when counting days already spent in a visa-limited region, when a reservation or cancellation deadline needs recording, when a flight is cancelled or delayed, a bag goes missing, a passport is stolen or a claim has to be filed, when deciding which destination to take next against a season and a budget, when travelling with children, a group, elderly parents or a pet, when a stay runs past a month or needs per-diem handling, or when points or elite status are about to expire. Not for building one trip's day-by-day itinerary (`travel-planning`), fare search (`flight`), accommodation search (`booking`), rental cars (`car-rental`), or moving abroad for good (`expat`).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 19 files body ≈ 6 394 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 19. 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)
  • warning body-long SKILL.md body ≈ 6394 tokens (recommended < 5000); move details to references/
  • 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 69/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 60Tools and files. Uses tools (bash, read) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 5 branches
  • 70Execution cost. Instruction body is 6394 tokens
  • 100Steps. 42 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 tags): a typed call is more reliable

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
  • +3Description length 963: 120–800 characters recommended
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 42 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill is a coherent local travel archive, but it can automatically read, write, and delete sensitive local records across shared travel, booking, health, contact, pet, vehicle, and finance files without asking first.
LLM: suspicious (high) · 27 Jul 2026