SKILLEMALL.ai

AC expression-coach

个人表达能力训练教练。支持即兴话题练习(AI评分+反馈)、职场/社交场景角色扮演模拟、表达框架速查、 自定义话题管理、进步追踪与数据分析、每日表达力Tips推送。 语音优先,通过 Whisper 转写分析口语特征(填充词、停顿、流畅度)。 支持飞书 Bitable 自动记录练习数据(可选)。 触发关键词:练口才、表达训练、即兴话题、场景模拟、表达框架、沟通练习、演讲练习、怎么说、话术、 说服、汇报练习、添加话题、自定义话题、查看进步、我的数据、练习报告。

ClawHub Agent Skills author: Andre v1.1.0 MIT-0 7 files body ≈ 2 355 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
53/100
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

  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: 7. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 131 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2355 tokens
  • 100Running it twice. No mutating operations
  • 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

  • +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
  • -227 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 229: enough signal without eating the budget
  • +4Structure: 49 headings
  • +3Step-by-step instructions: 131 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This speech-coaching skill is purpose-aligned, but it needs review because it can automatically save voice recordings, transcripts, scores, and speaking-analysis data to Feishu when tracking is enabled.
LLM: suspicious (high) · VirusTotal: · 29 May 2026