SKILLEMALL.ai

AB onionclaw

Search the Tor dark web, fetch .onion hidden-service pages, rotate Tor identities, and run structured multi-step OSINT investigations. Use when the user asks to search the dark web, investigate .onion sites, check whether data appeared on the dark web, fetch a .onion URL, look up leaked credentials, investigate ransomware groups, or conduct any Tor-based threat intelligence or OSINT task.

ClawHub Agent Skills author: JacobJandon v2.1.13 MIT-0 2 files body ≈ 2 845 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, running it twice

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
86
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Failures and branches w 10
55
the three weakest of ten parameters · all ten

How to improve

    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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Risky intent intent-offensive-security SKILL.md:8
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      leaked credentials, investigate ransomware groups, or conduct any Tor-based
    • low Risky intent intent-offensive-security SKILL.md:182
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (documentation table row)
      | `ransomware` | Malware / C2 / MITRE ATT&CK TTPs, victim orgs, indicators |
      table
    • low Risky intent intent-offensive-security SKILL.md:209
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (documentation table row)
      | `--mode MODE` | `threat_intel` | `threat_intel` / `ransomware` / `personal_identity` / `corporate` |
      table
    • low Risky intent intent-offensive-security SKILL.md:267
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      python3 {baseDir}/pipeline.py --query "ransomware hospital 2026" --watch --interval 6
      quoted
    • low Risky intent intent-offensive-security SKILL.md:299
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      ### "Investigate ransomware group X"
      quoted

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

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 65/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, web, python, node) 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. 18 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2845 tokens
    • 100Progress reporting. Reports progress

    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 391: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 18 items
    • +3Output format is stated explicitly
    • +4Has examples (18 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    OnionClaw is a coherent dark-web OSINT skill, but it asks for high-impact Tor, LLM, persistence, and setup authority while the executable scripts it references are not included for review.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026