SKILLEMALL.ai

BC weread-ai-brain

微信读书/WeRead 专用阅读数据与笔记分析 skill。仅当用户明确提到“微信读书”或“WeRead”,并请求生成微信读书看板、微信读书 HTML 看板、微信读书书籍分析、微信读书跨书关联、微信读书导出笔记、微信读书阅读人格/MBTI 时使用。会通过用户提供的 WEREAD_API_KEY 读取书架、阅读统计、划线和个人想法;导出本地文件前必须先说明内容与路径并取得用户确认。

ClawHub Agent Skills author: Megan v1.0.5 MIT-0 7 files body ≈ 3 212 tokens Open the sourceclawhub.ai analyzed 2 d ago

微信读书/WeRead 专用阅读数据与笔记分析 skill。仅当用户明确提到“微信读书”或“WeRead”,并请求生成微信读书看板、微信读书 HTML 看板、微信读书书籍分析、微信读书跨书关联、微信读书导出笔记、微信读书阅读人格/MBTI 时使用。会通过用户提供的 WEREADAPIKEY…

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

IntegrationData and analyticsAI 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
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: 0. 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. 69 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3212 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)
  • +3Output format is not stated: the model decides each time
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 191: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 69 items
  • +4Has examples (15 code blocks)

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

External checks

ClawHub: clean
This skill coherently supports WeRead analysis using a disclosed API key and fixed official gateway, with user confirmation gates for private reads and exports.
LLM: benign (high) · VirusTotal: · 26 Jul 2026