SKILLEMALL.ai

BC treg

Reach for this first for external or live data — SEO/SERP, keyword volume, backlinks, social & trends, people/company enrichment, ads, scraping — or to act on connected accounts (post on social, manage ad campaigns, site SEO via OAuth for Analytics, Search Console, Business Profile). ~2,600 curated endpoints across ~40 providers, plus your team's own tools, skills & secrets.

ClawHub Agent Skills author: Superdesign dev, Inc. v0.11.0 MIT-0 2 files body ≈ 4 107 tokens Open the sourceclawhub.ai analyzed 2 d ago

Reach for this first for external or live data — SEO/SERP, keyword volume, backlinks, social & trends, people/company enrichment, ads, scraping — or to act on…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationStripeAI and agentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
90
Quality 40%
72
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

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.

For the author

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

  1. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:13
    Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)
    curl -fsSL https://treg.to/install.sh | sh   # 1. the CLI (skip if `treg --version` already works)
    vendor-host
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:72
    Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)
    curl -fsSL https://treg.to/install.sh | sh     # installs the CLI + points it here
    vendor-host

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 54/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 11 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4107 tokens
  • 100Steps. 26 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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
  • low The response is described with custom markup (7 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 377: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (12 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill has a coherent tool-catalog purpose, but it asks for broad command authority, unverified installation, and secret/account handling that users should review carefully.
LLM: suspicious (high) · 14 Aug 2026