SKILLEMALL.ai

AC chinese-naming-master

Chinese Naming Master (天衡命名宗师), creating culturally rich Chinese personal names. 中文起名大师,为中国人创造富有文化底蕴的人名。 Triggers when users need: (1) newborn baby naming 新生儿起名, (2) adult name change 成人改名, (3) name analysis 名字分析, (4) any Chinese naming request based on traditional philosophy, I Ching, Five Elements, classical poetry, phonology and psychology. 当用户需要以下帮助时触发:为新生儿起中文名、成人改名、分析中文名字优劣、 基于传统哲学/周易/五行/古典诗词/音韵学/心理学的中文人名命名,含字辈排行命名。 Keywords 触发关键词: 起名、取名、命名、改名、字辈、族谱、辈分, Chinese name, baby name, name meaning, Five Elements 五行, Eight Characters 八字, 生辰, Zodiac 生肖, generational name 字辈排行. Personal names only — no brand, company, or product naming. 仅限人名——不接受品牌、公司或产品命名。

ClawHub Agent Skills author: longge0516 v1.0.5 MIT-0 3 files body ≈ 480 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorInfrastructureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 3. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 480 tokens
    • 100Running it twice. No mutating operations

    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 660: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 35 items
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is an instruction-only Chinese personal-name helper that asks for birth and family details but shows no code execution, storage, network sharing, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026