SKILLEMALL.ai

BC arabic-threat-intel

The only Arabic-first OSINT and threat intelligence skill. Monitor Arabic-language threat actor channels on Telegram, generate bilingual threat reports, search the dark web via Tor, and enumerate subdomains via Certificate Transparency logs. Works for any region — Middle East, Africa, Asia, or global. No API keys required.

ClawHub Agent Skills author: Kw.Hades- Creative Labs v1.0.1 MIT-0 4 files body ≈ 750 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency

IntegrationTelegramInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
70
Run on models
none yet
Process rating
C
60/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Consistency w 8
40
the three weakest of ten parameters · all ten

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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:61
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    Use arabic-threat-intel report "ransomware" --lang both
    quoted

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "validation"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 60/100

  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (arabic-threat-intel) differs from the folder (threat-intel)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 12 steps
  • 100Execution cost. Instruction body is 750 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 324: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 12 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +1License stated

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

External checks

ClawHub: clean
This skill performs the advertised passive threat-intelligence lookups, with some overbroad declared local permissions users should notice.
LLM: benign (high) · VirusTotal: · 29 May 2026