SKILLEMALL.ai
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BC ocas-imagine

Art-direction engine for text-to-image generation. Separates Style from Content to keep aesthetic identity consistent across an image series. Use when generating, rendering, or illustrating images (especially across a series), capturing the style of a reference image for reuse, or producing an image in a named/saved style. Not for captioning, image analysis for decisions (use ocas-look), or photo editing.

ClawHub Hermes author: Indigo Karasu v1.0.0 MIT-0 23 files · 1 script body ≈ 3 640 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Art-direction engine for text-to-image generation.

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorAI and agentsWriting and documentsMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. 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
  • 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: 22. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 408 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "includes"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 2 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 67 steps
  • 100Execution cost. Instruction body is 3640 tokens
  • 100Progress reporting. Reports progress
  • 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 (3 tags): a typed call is more reliable
  • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

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
  • +3Output format is not stated: the model decides each time
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 408: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 67 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (12 of 13)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
This is mostly an image art-direction skill, but it also ships a silent self-update path that can pull from GitHub and discard local repository changes without clear user consent.
LLM: suspicious (high) · 23 Sept 2026