SKILLEMALL.ai

BC real-browser-qa-ceki

QA and security testing via real Chrome browser sessions — realistic user simulation, vulnerability discovery, cross-browser inconsistency detection. Pre-flight: sessions → my-browsers → search. Type with `--natural`, probe with `snapshot`, distinguish insufficient_funds vs busy. Generic marketplace + env-driven self mode.

ClawHub Agent Skills author: iWedmak Om v1.0.0 MIT-0 73 files · 1 script body ≈ 8 894 tokens Open the sourceclawhub.ai analyzed 2 d ago

QA and security testing via real Chrome browser sessions — realistic user simulation, vulnerability discovery, cross-browser inconsistency detection.

As a process C 59/100 · Has gaps — weak spots: result and completion, consistency, execution cost

IntegrationSoftware developmentCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: QA and security testing via real Chrome browser sessions — realist… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning body-long SKILL.md body ≈ 8894 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 59/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (real-browser-qa-ceki) differs from the folder (real-browser-qa-ceki-main)
  • 40Execution cost. Instruction body is 8894 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 42 steps
  • 100Failures and branches. 2 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 21 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (26 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
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 324: enough signal without eating the budget
  • +4Structure: 67 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (32 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
This real-browser QA skill is mostly disclosed, but it needs Review because bundled profiles include third-party signup, CAPTCHA delegation, mailbox verification, and social engagement automation beyond owned-site testing.
LLM: suspicious (high) · 30 Jul 2026