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CC frame-logo-outro

Segmented logo assembly, glow bloom, and tagline reveal for video outros or brand closing frames.

nexu-io/open-design Hermes author: nexu-io Apache-2.0 3 files body ≈ 392 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Segmented logo assembly, glow bloom, and tagline reveal for video outros or brand closing frames.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMedia and videotype and topics are labelled automatically from the skill text
Runs in: Hermes Agent
JSON
Technical rating
C
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
52
Run on models
none yet
Process rating
C
56/100
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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 97 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "zh_name"
  • note frontmatter-key unknown frontmatter key "en_name"
  • note frontmatter-key unknown frontmatter key "emoji"
  • note frontmatter-key unknown frontmatter key "zh_description"
  • note frontmatter-key unknown frontmatter key "en_description"
  • note frontmatter-key unknown frontmatter key "scenario"
  • note frontmatter-key unknown frontmatter key "aspect_hint"
  • note frontmatter-key unknown frontmatter key "featured"
  • note frontmatter-key unknown frontmatter key "recommended"
  • note frontmatter-key unknown frontmatter key "example_id"
  • note frontmatter-key unknown frontmatter key "example_name"
  • note frontmatter-key unknown frontmatter key "example_format"
  • note frontmatter-key unknown frontmatter key "example_tagline"
  • note frontmatter-key unknown frontmatter key "example_desc"
  • note frontmatter-key unknown frontmatter key "example_source_url"
  • note frontmatter-key unknown frontmatter key "example_source_label"
  • note frontmatter-key unknown frontmatter key "od"

Process rating: all ten parameters 56/100

  • 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. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 392 tokens

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 97: 120–800 characters recommended
  • +4Structure: 0 headings, hard to scan
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Step-by-step instructions: 16 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.