SKILLEMALL.ai

BC art-critique

help artist doing art critique for their works in any medium (image, text, audio, video, installation, performance), giving outside perspectiive via abundant real aesthetic practices, drawing on a curated library of art theory, art history, cases, and events to enrich the dialogue. Triggered by 'critique', 'crit', 'critic', 'help me review my art work', 'talk about your feeling about my work', etc.

ClawHub Agent Skills author: iiiantower v1.0.1 MIT-0 28 files body ≈ 3 703 tokens Open the sourceclawhub.ai analyzed 2 d ago

help artist doing art critique for their works in any medium (image, text, audio, video, installation, performance), giving outside perspectiive via abundant…

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerMedia and videoResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
95
Quality 40%
72
Run on models
none yet
Process rating
C
60/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Edit Bash

Files scanned: 28. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 60/100

  • 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
  • 40Consistency. Frontmatter name (art-critique) differs from the folder (art-critique-skill)
  • 50When it triggers. No condition that starts the skill
  • 85Steps. 35 steps, 2 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 3 branches, has a failure section
  • 100Execution cost. Instruction body is 3703 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (9 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 401: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 35 items
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This skill is a disclosed art-critique note-taking workflow, with local session files as an expected part of its purpose and no evidence of hidden exfiltration or destructive behavior.
LLM: benign (high) · VirusTotal: · 7 Jun 2026