SKILLEMALL.ai

BC sovereign-docker-wizard

Docker optimization expert. Analyzes Dockerfiles for security and performance, generates multi-stage builds, optimizes image size, creates docker-compose configs, and identifies container misconfigurations.

modbender/skill-library-mcp Agent Skills author: modbender MIT 3 files body ≈ 8 485 tokens Open the sourcegithub.com analyzed 2 d ago

Docker optimization expert.

As a process C 53/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, execution cost

AnalyzerDockerPostgreSQLGitHubInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
96
Quality 40%
62
Run on models
none yet
Process rating
C
53/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
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.
  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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-password-literal EXAMPLES.md:513
    Hard-coded password / key literal (may be an example) (test fixture / example file)
    ENV API_KEY=sk-l…456
    fixture
  • low Secrets in code secret-password-literal EXAMPLES.md:559
    Hard-coded password / key literal (may be an example) (test fixture / example file)
    ENV API_KEY=sk-l…456
    fixture
  • low Secrets in code secret-password-literal SKILL.md:456
    Hard-coded password / key literal (may be an example) (placeholder value)
    ENV API_KEY=sk-1…def
    placeholder
  • low Exfiltration read-dotenv SKILL.md:459
    Reads a .env file (Dockerfile instruction (build context, not runtime exfiltration); documentation of a security skill)
    COPY .env /app/.env
    Dockerfilesecurity skill

Files scanned: 3. 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 ≈ 8485 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 53/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 9 mutating operations with no state check
  • 40Execution cost. Instruction body is 8485 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 53 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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)
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 206: enough signal without eating the budget
  • +4Structure: 67 headings
  • +3Step-by-step instructions: 53 items
  • +3Output format is stated explicitly
  • +4Has examples (53 code blocks)

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