SKILLEMALL.ai

BD linkfox-google-trend-get-trend-by-keys

Google Trends关键词搜索热度对比与趋势分析,支持全球区域和自定义时间范围。当用户提到谷歌趋势、关键词随时间变化的热度、搜索兴趣对比、关键词趋势分析、季节性趋势检测、区域搜索热度、关键词热力图、多个关键词在Google上的对比、Google Trends, keyword popularity comparison, search trends, seasonal analysis, regional popularity, keyword comparison时触发此技能。即使用户未明确说"Google Trends",只要其需求涉及对比不同时间段或区域的关键词搜索热度趋势,也应触发此技能。

ClawHub Agent Skills author: linkfox-ai v1.0.6 MIT-0 6 files body ≈ 2 000 tokens Open the sourceclawhub.ai analyzed 3 d ago

Google Trends关键词搜索热度对比与趋势分析,支持全球区域和自定义时间范围。当用户提到谷歌趋势、关键词随时间变化的热度、搜索兴趣对比、关键词趋势分析、季节性趋势检测、区域搜索热度、关键词热力图、多个关键词在Google上的对比、Google Trends, keyword popularity…

As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerSoftware developmentData and analyticsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
73
Run on models
none yet
Process rating
D
47/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Dangerous commands cmd-shell-rc references/onboarding.md:13
    Writes to a shell startup file (quoted — discussed, not commanded)
    - macOS zsh:`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.zshrc && source ~/.zshrc`
    quoted
  • low Dangerous commands cmd-shell-rc references/onboarding.md:14
    Writes to a shell startup file (detector / deny-list definition)
    - Linux bash:`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.bashrc && source ~/.bashrc`
    detector

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")

Process rating: all ten parameters 47/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 85Steps. 34 steps, 3 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2000 tokens
  • low 10 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 305: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
The skill can do the advertised Google Trends lookup, but it also adds high-impact onboarding, billing, credential persistence, local storage, and automatic feedback reporting that need review before installation.
LLM: suspicious (high) · 14 Aug 2026