AC claude-designer
Produce thoughtful, well-crafted design artifacts (slide decks, interactive prototypes, hi-fi mockups, animated videos, landing pages, dashboards, marketing one-pagers) using HTML/CSS/JS/SVG as the medium. Use this skill whenever the user asks to "design", "mock up", "prototype", "make a deck", "make slides", "make a landing page", "create a dashboard", "visualize X", "build a UI", "build an interactive demo", or any request whose deliverable is a visual artifact rather than production code. Also trigger for requests like "recreate this UI", "explore options for X", "give me variations of Y", or when the user attaches screenshots/Figma/PRDs and wants a visual response. HTML is the tool; the medium varies — embody the right expert (slide designer, UX designer, animator, prototyper) for the task.
As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokenreferences/react-setup.md:13High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)<script src="https://unpkg.com/re…@….3.1/umd/react-dom.development.js" integrity="sha3…L9t+IBXm…uAm" crossorigin="anonymous"></script>
quoted -
low Secrets in code
secret-high-entropy-tokenreferences/react-setup.md:49High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)<script src="https://unpkg.com/re…@….3.1/umd/react-dom.development.js" integrity="sha3…L9t+IBXm…uAm" crossorigin="anonymous"></script>
quoted
Files scanned: 18. 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 63/100
- 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. 4 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 85Steps. 61 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 15 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3093 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 12 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 805: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 13 example trigger phrases
- +4Structure: 13 headings
- +3Step-by-step instructions: 61 items
- +4Reference files are cited in the instructions (8 of 8)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.