SKILLEMALL.ai

AC drawio-architecture

Use when generating or editing draw.io/diagrams.net architecture diagrams via MCP or native XML.

ClawHub Agent Skills author: Afonso Dutra Nogueira Filho v1.0.5 MIT-0 13 files body ≈ 5 152 tokens Open the sourceclawhub.ai analyzed 35 h ago

io/diagrams.net architecture diagrams via MCP or native XML.

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

GeneratorAWSGoogle CloudAzureKubernetesAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5152 tokens (recommended < 5000); move details to references/

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
  • 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
  • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5152 tokens
  • 100Steps. 61 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 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 21 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (13 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)
  • +3Description length 96: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 61 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)
  • +3All 2 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
The skill is a coherent draw.io diagram tool, but its setup helper can persistently change agent/IDE MCP settings to run an unpinned npm package and may print existing config contents.
LLM: suspicious (high) · 11 Sept 2026