SKILLEMALL.ai

AB claude-design

Design one-off HTML artifacts (landing, deck, prototype).

NousResearch/hermes-agent Hermes author: NousResearch MIT 1 file body ≈ 6 157 tokens Open the sourcegithub.com analyzed 2 d ago

Design one-off HTML artifacts (landing, deck, prototype).

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

ProcedureStripeNotionAI and agentstype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
B
68/100
Nearly there
Progress reporting w 2
0
Inputs and preconditions w 11
30
Running it twice w 4
30
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6157 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 68/100

  • 0Progress reporting. Says nothing while it works
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 10 mutating operations with no state check
  • 60Steps. 284 steps, 4 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Failures and branches. 4 branches
  • 70Execution cost. Instruction body is 6157 tokens
  • 100Tools and files. No external tools needed
  • 100When it triggers. States when to use and when not to
  • low 30 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 57: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 284 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.