AF google-search-serp
Extracts Google Search results page (SERP) data including organic results, paid ads, related searches, People Also Ask questions, AI Overview text, and total result count from google.com. Use when user mentions Google search results, SERP scraping, google search data, search engine results page, organic rankings, keyword SERP, Google SERP extraction, scrape Google search, Google search API alternative, SEO ranking data, paid search ads, PPC ads on Google, Google search monitoring, keyword research, search results export, check Google rankings, what shows up on Google, search engine scraper, google results checker.
Extracts Google Search results page (SERP) data including organic results, paid ads, related searches, People Also Ask questions, AI Overview text, and total…
As a process F 54/100 · Will not run — References files that are not bundled: scripts/*.py
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/*.py
Process rating: all ten parameters 54/100
- 0Tools and files. 1 referenced file(s) missing: scripts/*.py
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 23 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 1860 tokens
- low 10 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
- +1No license
- +2Single-language instructions
- +3Description length 621: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.