SKILLEMALL.ai

BB target-product-data

Search Target.com, browse a category, read product detail by TCIN and pull reviews with the rating breakdown as structured JSON. 4 endpoints, 1 credit each, store-aware pricing via store_id.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: scavio-ai v1.0.4 MIT-0 2 files body ≈ 2 514 tokens Open the sourceclawhub.ai analyzed 4 d ago

Search Target.com, browse a category, read product detail by TCIN and pull reviews with the rating breakdown as structured JSON. 4 endpoints, 1 credit each…

As a process B 77/100 · Nearly there — weak spots: inputs and preconditions, running it twice

ProcedureAI and agentsCommerceData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
82
Quality 40%
75
Run on models
none yet
Process rating
B
77/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Result and completion w 14
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • high Concealment en-hide-from-user SKILL.md:169
    Instruction to hide actions from the user
    - **`/reviews` returns 8 review bodies maximum**, regardless of what `review_count` on the product says. `limit` only trims that set further. There is no `page` and no `offset` parameter. Never tell t

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 77/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 37 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2514 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 190: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 37 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill is a straightforward Target product-data helper that uses a disclosed Scavio API key and does not install code or persist access.
LLM: benign (high) · VirusTotal: · 9 Sept 2026