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Audio spectrograms/features (mel, chroma, MFCC) via CLI.

NousResearch/hermes-agent Hermes author: NousResearch MIT 1 file body ≈ 498 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

As a process C 63/100 · Has gaps — weak spots: when it triggers, failures and branches, progress reporting

IntegrationSoftware developmentInfrastructureDesigntype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
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.
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 description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "prerequisites"

Process rating: all ten parameters 63/100

  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 75Steps. 3 steps
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 498 tokens
  • 100Running it twice. No mutating operations

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 56: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 3 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: 72.