SKILLEMALL.ai

AA claim-verifier

Verify external factual claims in draft content before publishing or sending. Produces a structured claim verification report with evidence links.

ClawHub Agent Skills author: jernejcicorbin-hub v1.0.2 MIT-0 7 files · 2 scripts body ≈ 2 229 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process A 80/100 · Runs to the end — weak spots: running it twice, progress reporting

AnalyzerInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
87
Run on models
none yet
Process rating
A
80/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
When it triggers w 12
50
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

    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
    • medium Dangerous commands cmd-shell-rc SKILL.md:52
      Writes to a shell startup file
      echo 'export PRISMFY_API_KEY="ss_live_your_key_here"' >> ~/.bashrc

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 80/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 115 steps
    • 100Failures and branches. 10 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2229 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 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 146: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 115 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a coherent fact-checking helper that uses a disclosed Prismfy API key and optional reminder hook, with privacy and credential-handling cautions but no artifact-backed malicious behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026