SKILLEMALL.ai

AC oiiotool

Image processing with oiiotool CLI — format conversion (EXR, TIFF, DPX, PNG, JPEG, HDR), OCIO/ACES color management and display transforms, exposure adjustment, resize/crop, compositing, EXR sequence to video, texture baking, image comparison, and batch/sequence operations. Use when working with image files, EXR sequences, color spaces, or HDR content.

ClawHub Agent Skills author: oumad v0.1.1 7 files body ≈ 4 565 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 50/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

IntegrationInfrastructureMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
50/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 50/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4565 tokens
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • low 21 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)
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 354: enough signal without eating the budget
    • +4Structure: 36 headings
    • +3Step-by-step instructions: 14 items
    • +3Output format is stated explicitly
    • +4Has examples (33 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This is a coherent local image-processing skill, but users should be careful because its examples and helper scripts can overwrite output files.
    LLM: benign (high) · VirusTotal: · 29 May 2026