SKILLEMALL.ai

AB merklemap-osint

Full-featured OSINT reconnaissance using the MerkleMap API: subdomain enumeration, SSL/TLS certificate inspection, certificate deep-dive, real-time CT log monitoring, typosquatting detection, risk scoring, and professional HTML/JSON report generation. Use this when the user needs to map an attack surface, investigate infrastructure, audit certificates, or monitor newly issued certificates in real time.

ClawHub Agent Skills author: [DL] v3.0.1 MIT-0 4 files body ≈ 7 933 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 71/100 · Nearly there — weak spots: inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
B
71/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Result and completion w 14
60
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7933 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 71/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Tools and files. Uses tools (write, web) 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
  • 70Execution cost. Instruction body is 7933 tokens
  • 100Steps. 124 steps
  • 100Failures and branches. 16 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • 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)
  • +2Single-language instructions
  • +3Description length 405: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 124 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This is a coherent MerkleMap OSINT skill that uses a declared API key and creates local reports only as part of its advertised reporting features.
LLM: benign (high) · VirusTotal: · 29 May 2026