SKILLEMALL.ai

CD quicker-connector

与 Quicker 自动化工具集成,读取、搜索和执行 Quicker 动作列表。支持 CSV 和数据库双数据源,智能匹配用户需求并调用本地 QuickerStarter 执行。同时提供数据维护能力:解析维护工具全量备份(export 目录)、按配置映射定位/读取/修改快捷键、轮盘、手势、组合键等所有配置。

ClawHub Agent Skills author: Awam M Wang v1.5.0 MIT-0 35 files · 15 scripts body ≈ 3 449 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

与 Quicker 自动化工具集成,读取、搜索和执行 Quicker 动作列表。支持 CSV 和数据库双数据源,智能匹配用户需求并调用本地 QuickerStarter 执行。同时提供数据维护能力:解析维护工具全量备份(export 目录)、按配置映射定位/读取/修改快捷键、轮盘、手势、组合键等所有配置。

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureExcelPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
61
Run on models
none yet
Process rating
D
43/100
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Obfuscation obf-base64-blob data/quicker_export_map.json:264
    Long base64-looking blob (quoted — discussed, not commanded)
    "name": "OpenPopWithMiddleClick/XBut…ick/XBut…ick/CtrlMiddleClick/CtrlClick/CtrlRightClick/LongRightPress/LongMiddlePress/RightPressMove",
    quoted
  • low Obfuscation obf-base64-blob data/quicker_export_map.json:268
    Long base64-looking blob (quoted — discussed, not commanded)
    "name": "EnableCircleMenu/CircleMenuTrigger/CircleMenuSize/CircleMenuFontSize/Circ…unt/CircleMenuTimeoutMs/CircleMenuAutoMoveCursor/CircleMenuShowExternalWhenPopup",
    quoted

Files scanned: 33. 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 "trigger"
  • note frontmatter-key unknown frontmatter key "examples"
  • note frontmatter-key unknown frontmatter key "requirements"
  • note frontmatter-key unknown frontmatter key "settings"
  • note frontmatter-key unknown frontmatter key "system_prompt"
  • note frontmatter-key unknown frontmatter key "thinking_model"
  • note frontmatter-key unknown frontmatter key "security_notes"

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 46 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3449 tokens
  • low 15 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -228 emoji in the instructions: noise for the model
  • -33 of 11 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 153: enough signal without eating the budget
  • +4Structure: 36 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (19 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This skill is useful for Quicker automation, but it needs review because it can run local actions and edit settings while some network and confirmation behavior is under-disclosed.
LLM: suspicious (high) · 6 Oct 2026