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AB serpapi-mcp

Run SerpAPI searches via SerpAPI's MCP server using mcporter. Use when the user asks to search the web with SerpAPI/SerpAPI MCP, wants SerpAPI inside Clawdbot, or to use the /serp command.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files · 1 script body ≈ 1 164 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Run SerpAPI searches via SerpAPI's MCP server using mcporter.

As a process B 73/100 · Nearly there — weak spots: running it twice, progress reporting

ProcedureAirtableAI 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
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
80
Run on models
none yet
Process rating
B
73/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Tools and files w 18
60
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration exfil-secret-in-url scripts/fetch_ai_overview.mjs:36
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      const url = `https://serpapi.com/google-ai-overview-api?api_key=…&token=…&output=…
      placeholder

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 73/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 77 steps, 3 vague phrases
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1164 tokens
    • low The response is described with custom markup (3 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)
    • +4No input/output examples
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 188: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 77 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.