SKILLEMALL.ai

BD openclaw-prompt-shield

Local input-hardening scanner for OpenClaw agents. Pattern-based detection across 9 categories of LLM input risks, with combined-signal scoring and caller-supplied whitelists. Returns risk score 0-100, matched categories, a suggested sanitized version, and a safe-to-process verdict. Pure Python standard library, no remote calls, no API keys, no LLM.

ClawHub Agent Skills author: Gopendra Sharma v0.4.4 MIT-0 12 files · 1 script body ≈ 2 958 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
87
Quality 40%
74
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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.

Exfiltration 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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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
  • medium Exfiltration exfil-read-secret-files scripts/_patterns.py:274
    Reads credential / secret files (detector / deny-list definition)
    (r"\b(?:cat|less|more|head|tail)\s+(?:/etc/passwd|/etc/shadow|/proc/self|~/\.ssh/|~/\.aws/|~/\.gnupg/|~/\.config/)", "tool_abuse"),
    detector
  • low Dangerous commands cmd-pipe-to-shell scripts/_patterns.py:272
    Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition; string literal in code, not executed)
    (_ws("execute", r"(?:curl|wget|bash|sh|powershell|cmd|python|perl|ruby)"), "tool_abuse"),
    detectorcode literal
  • low Dangerous commands cmd-pipe-to-shell scripts/_patterns.py:273
    Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition; string literal in code, not executed)
    (_ws("run", r"(?:curl|wget|bash|sh|powershell|cmd)", r"[-/]"), "tool_abuse"),
    detectorcode literal

A further 2 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 12. 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 43/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 50 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2958 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 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)
  • +3Output format is not stated: the model decides each time
  • -31 of 6 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 351: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 50 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This is a local prompt-injection scanning skill whose file access and pattern lists match its stated defensive purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026