SKILLEMALL.ai

AC results-vocabulary-lexis-advisor

用于诊断英文心理学论文 Results 部分的学术词汇与搭配质量,包括口语化表达识别、学术动词准确性、图表邀请语规范性、结果描述词恰当性、术语一致性和搭配自然度。本 Skill 是 Results 写作诊断总 Skill 的第 4 个子 Skill(成员 D),在 results-structure-diagnoser(A)、results-statistics-convention-checker(B)、results-tense-grammar-checker(C)之后执行。

ClawHub Agent Skills author: ziyi-z-z v1.0.0 MIT-0 8 files body ≈ 1 074 tokens Open the sourceclawhub.ai analyzed 3 d ago

用于诊断英文心理学论文 Results 部分的学术词汇与搭配质量,包括口语化表达识别、学术动词准确性、图表邀请语规范性、结果描述词恰当性、术语一致性和搭配自然度。本 Skill 是 Results 写作诊断总 Skill 的第 4 个子 Skill(成员 D),在…

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
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: 8. 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 62/100

  • 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
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 52 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1074 tokens
  • 100Running it twice. No mutating operations
  • low 10 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 242: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 52 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
The skill is a coherent academic writing advisor, but one bundled reference PDF contains under-disclosed active JavaScript content.
LLM: suspicious (medium) · VirusTotal: · 26 Aug 2026