SKILLEMALL.ai
GitHub ↗ RU Sign in

AC google-search-tool-free

基于 Google Custom Search Engine 的联网搜索工具，支持实时信息检索与结果结构化输出，适合个人研究与学习使用。Use when 需要SEO优化、关键词分析、排名提升、搜索流量优化时使用。不适用于黑帽SEO手段。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互，无需复杂配置即开即用。

ClawHub Agent Skills author: 天轰穿 v1.0.3 MIT-0 2 files body ≈ 1 598 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

基于 Google Custom Search Engine 的联网搜索工具，支持实时信息检索与结果结构化输出，适合个人研究与学习使用。Use when 需要SEO优化、关键词分析、排名提升、搜索流量优化时使用。不适用于黑帽SEO手段。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互，无需复杂配置即开即用。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGoogle CloudSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
53/100
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

    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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "tools"

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1598 tokens
    • 100Running it twice. No mutating operations
    • low 15 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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 159: enough signal without eating the budget
    • +4Structure: 41 headings
    • +3Step-by-step instructions: 39 items
    • +4Has examples (13 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    This appears to be a Google search helper rather than malware, but its documentation asks for broad command and file authority with inconsistent scope and credential handling.
    LLM: suspicious (high) · 29 Aug 2026