SKILLEMALL.ai

BC shell-security-ultimate

Classify every shell command as SAFE, WARN, or CRIT before your agent runs it. The classification is instruction-only and runs nothing. The package also ships optional installer scripts that MODIFY SOURCE CODE in an OpenClaw checkout you point them at — they refuse non-OpenClaw trees, verify the whole edit in a temp file before touching the real one, back up, require --yes, offer --dry-run, never rebuild unless you ask, and ship with an unpatch off-switch that validates its range instead of deleting between markers. Nothing is patched by installing this skill. Built for the TinkerClaw fork — github.com/globalcaos/tinkerclaw. See Permissions, Data Flow & Consent.

ClawHub Agent Skills author: Oscar Serra v2.3.2 MIT-0 8 files · 3 scripts body ≈ 3 126 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubSoftware developmentAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
98
Quality 40%
75
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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 · 2

✓ No critical or high findings

Medium and low: 2

✓ Guard found no suspicious behaviour. 2 matches are attack strings quoted in this security skill's own documentation.

Files scanned: 6. 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 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, git, python) that frontmatter does not declare
  • 70Failures and branches. 4 branches
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3126 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 670: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (3 code blocks)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
The skill is a disclosed command-safety helper; its optional source-code patch is high-impact but opt-in and reversible, with no evidence of hidden network, credential, or destructive behavior.
LLM: benign (high) · VirusTotal: · 10 Sept 2026