AB brightdata-cli
Guide for using the Bright Data CLI (`brightdata` / `bdata`) to scrape websites, search the web, extract structured data from 40+ platforms, manage proxy zones, and check account budget. Use this skill whenever the user wants to scrape a URL, search Google/Bing/Yandex, extract data from Amazon/LinkedIn/Instagram/TikTok/YouTube/Reddit or any other platform, check their Bright Data balance or zones, or do anything involving web data collection from the terminal. Also trigger when the user mentions brightdata, bdata, web scraping CLI, SERP API, or wants to install Bright Data skills into their coding agent.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
medium Dangerous commands
cmd-pipe-to-shellreferences/commands.md:9Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)curl -fsSL https://cli.brightdata.com/install.sh | bash
vendor-host -
medium Dangerous commands
cmd-pipe-to-shellSKILL.md:16Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)curl -fsSL https://cli.brightdata.com/install.sh | bash
vendor-host -
low Dangerous commands
cmd-pipe-to-shellSKILL.md:280Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation table row; the skill's own vendor host)| CLI not found | Install with `npm i -g @brightdata/cli` or `curl -fsSL https://cli.brightdata.com/install.sh \| bash` |
tablevendor-host
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 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (brightdata-cli) differs from the folder (brightdata-brightdata-cli)
- 60Tools and files. Uses tools (bash, web) 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
- 100Steps. 10 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Execution cost. Instruction body is 2042 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 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)
- +1No license
- +2Single-language instructions
- +3Description length 611: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 10 items
- +3Output format is stated explicitly
- +4Has examples (15 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.