SKILLEMALL.ai

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普通话与十一种中文方言双向对照查询技能。支持哈尔滨话、河南话、湖南话、天津话、北京话、上海话、广东话、东营方言、重庆方言、闽南话、大连话与普通话的日常词汇对照。适用于AI方言对话、跨方言沟通、方言文化研究、文案本地化。含13333条词汇库。

ClawHub Agent Skills author: esnowxu v1.0.32 MIT-0 16 files · 2 scripts body ≈ 1 807 tokens Open the sourceclawhub.ai analyzed 2 d ago

普通话与十一种中文方言双向对照查询技能。支持哈尔滨话、河南话、湖南话、天津话、北京话、上海话、广东话、东营方言、重庆方言、闽南话、大连话与普通话的日常词汇对照。适用于AI方言对话、跨方言沟通、方言文化研究、文案本地化。含13333条词汇库。

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
46/100
Unfinished process
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

  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: 16. 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 46/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1807 tokens
  • 100Running it twice. No mutating operations
  • low 11 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)
  • +3Output format is not stated: the model decides each time
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 120: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (9 code blocks)

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

External checks

ClawHub: suspicious
This looks like a real dialect dictionary, but it also includes under-scoped cloud sync, recurring enrichment, credential access, and local chat-derived logging that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 13 Jun 2026