BD Investment Advisory Scripts & Talk-Point Assistant
AI-powered investment advisory scripts and talk-point generator for China wealth management — covers stock recommendations, fund allocation, market commentary, client objection handling, and compliance-compliant communication templates. Built for China securities brokers, wealth management advisors, and relationship managers. Keywords: investment advisory scripts, wealth management talk points, client communication, stock recommendations, fund sales scripts, compliance communication, China securities, 投顾话术, 财富管理, 客户沟通, 基金销售, 合规话术, 理财经理, 基金推荐, 资产配置, 客户维护, 异议处理, 营销话术.
AI-powered investment advisory scripts and talk-point generator for China wealth management — covers stock recommendations, fund allocation, market…
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: AI-powered investment advisory scripts and talk-point generator fo… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 41/100
- 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
- 40Consistency. Frontmatter name (Investment Advisory Scripts & Talk-Point Assistant) differs from the folder (security-rma-scripts)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 18 steps
- 100Execution cost. Instruction body is 3497 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 572: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.