SKILLEMALL.ai

BC hotel-price-monitor

酒店降价监控与多平台比价助手,同时搜索多个旅游平台实时价格帮你比价省钱,支持按酒店名称精确比价、按城市搜索酒店列表、创建降价监控任务,多旅游平台数据直连。暑期订酒店省钱,价格监控与实时比价

ClawHub Agent Skills author: 旅行技能 v1.1.6 MIT-0 4 files body ≈ 933 tokens Open the sourceclawhub.ai analyzed 2 d ago

酒店降价监控与多平台比价助手,同时搜索多个旅游平台实时价格帮你比价省钱,支持按酒店名称精确比价、按城市搜索酒店列表、创建降价监控任务,多旅游平台数据直连。暑期订酒店省钱,价格监控与实时比价

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 933 tokens
  • low 17 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)
  • +3Description length 94: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 60 items
  • +4Has examples (1 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
This hotel price skill mostly does what it advertises, but it needs review because it sends travel details through opaque proxy services using an embedded shared token and has commission-aware result ordering.
LLM: suspicious (high) · 26 Aug 2026