SKILLEMALL.ai

BF pricewin-hotel-search

Search hotels live across Agoda + Booking.com + Traveloka + OpenTravel with realtime pricing for specific dates. Use when user wants hotel prices for travel dates, comparing OTAs, or finding rooms.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: wenlambo v1.0.4 MIT-0 4 files body ≈ 1 662 tokens Open the sourceclawhub.ai analyzed 30 h ago

Search hotels live across Agoda + Booking.com + Traveloka + OpenTravel with realtime pricing for specific dates. Use when user wants hotel prices for travel…

As a process F 49/100 · Will not run — References files that are not bundled: ../pricewin-hotel-deal-finder/, ../pricewin-booking-assistant/

ProcedureGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
82
Quality 40%
78
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: ../pricewin-hotel-deal-finder/, ../pricewin-booking-assistant/
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. The text references files that are not there: add them or drop the references.
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 · 1

  • high Concealment en-hide-from-user SKILL.md:37
    Instruction to hide actions from the user
    **Never tell the user "loading/please wait" after 1-2 polls — that's premature.**

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../pricewin-hotel-deal-finder/
  • warning missing-ref reference to a missing file: ../pricewin-booking-assistant/

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: ../pricewin-hotel-deal-finder/, ../pricewin-booking-assistant/
  • 0Tools and files. 2 referenced file(s) missing: ../pricewin-hotel-deal-finder/, ../pricewin-booking-assistant/
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1662 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (4 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 197: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 17 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This documentation-only hotel search skill is coherent and disclosed, with the main trade-off being use of PriceWin's hosted closed-source backend for travel searches.
LLM: benign (high) · VirusTotal: · 9 Aug 2026