SKILLEMALL.ai

BD mcp-security-scan

当用户说『接了个MCP server不放心』『MCP工具能执行命令怕有风险』『怎么审计MCP权限』『第三方MCP会不会偷数据』,或要把某 MCP server(模型上下文协议)接进 agent、担心它是新攻击面时使用。把 MCP server 当『需审查的第三方』:扫工具清单里的 命令执行/文件系统写/网络外联/凭证暴露 四类风险,给风险评级与最小授权建议。理论根基:LGD 三律(有籍·有证·有门禁)。触发词:MCP安全、mcp security、MCP审计、MCP权限、第三方MCP、MCP风险、server扫描、协议安全。

ClawHub Hermes author: zhaoxinghua09-cell v1.0.0 MIT-0 7 files body ≈ 510 tokens Open the sourceclawhub.ai analyzed 2 d ago

当用户说『接了个MCP server不放心』『MCP工具能执行命令怕有风险』『怎么审计MCP权限』『第三方MCP会不会偷数据』,或要把某 MCP server(模型上下文协议)接进 agent、担心它是新攻击面时使用。把 MCP server 当『需审查的第三方』:扫工具清单里的…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSecurityAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
D
46/100
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

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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • warning description-long-hermes description is 265 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "title"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "copyright"
  • note frontmatter-key unknown frontmatter key "read_when"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 510 tokens
  • 100Running it twice. No mutating operations

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 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 265: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
The skill itself is a simple local MCP tool-list scanner, but its unpinned global install instructions create a supply-chain and persistence concern users should review first.
LLM: suspicious (medium) · VirusTotal: · 11 Sept 2026