SKILLEMALL.ai
GitHub ↗ RU Sign in

CC huashu-luxe-whitespace

A market-entry study for a luxury skincare brand entering Asia — segmentation, positioning, channel, and the phased plan. Built as a decision-grade consulting deck for client leadership.

nexu-io/open-design Agent Skills author: nexu-io Apache-2.0 4 files body ≈ 2 181 tokens Open the sourcegithub.com↗ analyzed 6 d ago

A market-entry study for a luxury skincare brand entering Asia — segmentation, positioning, channel, and the phased plan.

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

ProcedureMarketingData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
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.
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: 4. 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")
  • note frontmatter-key unknown frontmatter key "en_name"
  • note frontmatter-key unknown frontmatter key "zh_name"
  • note frontmatter-key unknown frontmatter key "en_description"
  • note frontmatter-key unknown frontmatter key "zh_description"
  • note frontmatter-key unknown frontmatter key "triggers"
  • 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
  • 55Failures and branches. 1 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2181 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 186: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 19 items
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.