SKILLEMALL.ai

AC wealth-management

财富管理技能套件:基金分析、客户报告、市场速览、理财规划、税务筹划、资产配置。 基金分析: 帮我分析下这只基金, 帮我看看这个基金怎么样, 业绩归因, 基金对比, 持仓分析; 客户报告: 客户报告, 季报, 持仓报告, 投资报告; 市场速览: 市场速览, 早盘速递, 行情分析, 市场概览; 理财规划: 帮我做个理财规划, 帮我规划下养老, 养老规划, 财务规划, 退休规划; 税务筹划: 税务筹划, 个税, 税优, 节税; 资产配置: 帮我做个资产配置方案, 帮我看下怎么配置, 大类资产, 再平衡, 配置策略。

ClawHub Agent Skills author: ebandao v0.1.0 MIT-0 9 files body ≈ 1 149 tokens Open the sourceclawhub.ai analyzed 3 d ago

财富管理技能套件:基金分析、客户报告、市场速览、理财规划、税务筹划、资产配置。 基金分析: 帮我分析下这只基金, 帮我看看这个基金怎么样, 业绩归因, 基金对比, 持仓分析; 客户报告: 客户报告, 季报, 持仓报告, 投资报告; 市场速览: 市场速览, 早盘速递, 行情分析, 市场概览; 理财规划…

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

ProcedureData and analyticsFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
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: 9. 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. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1149 tokens
  • 100Running it twice. No mutating operations

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 257: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
The skill is a coherent wealth-management assistant, but it handles sensitive financial client data and can write reports to Notion without clear consent, privacy, or retention controls.
LLM: suspicious (high) · 15 Aug 2026