AD excalidraw
Hand-drawn Excalidraw JSON diagrams — architecture, flow, sequence. Generate clean, well-laid-out charts with consistent box sizing, meaningful colors, and zero line crossings.
Hand-drawn Excalidraw JSON diagrams — architecture, flow, sequence.
As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- 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-hermesdescription is 176 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "dependencies"
Process rating: all ten parameters 45/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Consistency. Frontmatter name (excalidraw) differs from the folder (hermes-excalidraw)
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
- 85Steps. 87 steps, 1 vague phrases
- 100Execution cost. Instruction body is 3787 tokens
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 176: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 87 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (2 of 4)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.
External checks
ClawHub: suspicious
This diagram skill is coherent, but it makes third-party upload and browser-based screenshot verification part of the default workflow without enough user control or privacy warning.
LLM: suspicious (high) · VirusTotal: · 11 Jun 2026