SKILLEMALL.ai

BC content-security-filter

Prompt injection and malware detection filter for external content. Scans text, files, or URLs for 20+ attack patterns including instruction overrides, credential exfiltration, persona hijacking, encoded payloads, fake system messages, and invisible character injection. Returns JSON with risk level and sanitized text.

ClawHub Agent Skills author: Bryan Tegomoh, MD, MPH v1.0.0 MIT-0 3 files body ≈ 569 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, running it twice

AnalyzerAI and agentsSecurityInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
78
Run on models
none yet
Process rating
C
60/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Instruction override en-ignore-previous SKILL.md:14
    Instruction-override phrase ("ignore previous instructions") (documentation table row; documentation of a security skill)
    | Override attempts | "ignore previous instructions", "forget everything" |
    tablesecurity skill
  • low Risky intent intent-offensive-security SKILL.md:22
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Credential harvesting | "provide your password/token/secret" |

A further 3 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 3. 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 60/100

  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 569 tokens

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 319: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 6 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: clean
This is a defensive content-scanning skill with disclosed file, text, stdin, and URL scanning behavior that matches its stated purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026