SKILLEMALL.ai

BC docker-toolkit-free

面向个人开发者的Docker容器管理工具。支持镜像构建与拉取、容器

ClawHub Agent Skills author: 天轰穿 v1.0.0 MIT-0 2 files body ≈ 1 401 tokens Open the sourceclawhub.ai analyzed 21 h ago

面向个人开发者的Docker容器管理工具。支持镜像构建与拉取、容器

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationDockerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
95
Quality 40%
49
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
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.

Dangerous commands 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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:139
    Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)
    # Linux: curl -fsSL https://get.docker.com | sh
    vendor-host

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Map keys must be unique at line 24, column 1: suggested_price: "9.9 CNY/per_use" tools: ["read", "write", "exec"] ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-short description under 40 chars: too little signal for triggering
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "edition"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "pricing_tier"
  • note frontmatter-key unknown frontmatter key "pricing_model"
  • note frontmatter-key unknown frontmatter key "suggested_price"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1401 tokens
  • 100Running it twice. No mutating operations
  • low 11 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)
  • +3Description length 33: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.

External checks

ClawHub: suspicious
This Docker skill mostly matches its stated purpose, but its trigger text is overbroad and it advertises disruptive Docker actions without enough user-control guidance.
LLM: suspicious (high) · 23 Jul 2026