SKILLEMALL.ai

CB security-audit

Security audit — save tampering, cheat vectors, network exploits, data exposure, input validation. Before public or multiplayer release.

Donchitos/Claude-Code-Game-Studios Claude Code author: Donchitos MIT 1 file body ≈ 5 438 tokens Open the sourcegithub.com↗ analyzed 28 h ago

Security audit — save tampering, cheat vectors, network exploits, data exposure, input validation.

As a process B 66/100 · Nearly there — weak spots: result and completion, inputs and preconditions

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
98
Quality 40%
62
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
40
When it triggers w 12
50
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.
  2. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Broad scope meta-dynamic-shell SKILL.md:10
    Shell command executed automatically when the skill loads (Claude Code !`cmd` preamble)
    !`bash "${CLAUDE_SKILL_DIR}/../../hooks/yaml-helper.sh" resolve_config --keys automation,workflow`
  • low Risky intent intent-offensive-security SKILL.md:439
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **This is not a penetration test** — this audit covers common patterns; a real pentest by a human security professional is recommended before any competitive or monetised multiplayer launch

Files scanned: 1. 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")
  • warning body-long SKILL.md body ≈ 5438 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 52): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 66/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5438 tokens
  • 85Steps. 43 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (4 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 136: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 43 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.