BC Insurance Agent Intelligent Trainer
AI-powered insurance agent training coach — auto-parses product docs, generates question banks, assesses agent skill levels (beginner/intermediate/advanced), schedules personalized daily training based on client visits, and delivers interactive role-play sessions. Updated for 2025-2026: covers predinig rate cut (3.0%) impact on sales scripts, new health insurance regulation, PIPL-compliant customer communication, and benchmark against AIA, Ping An, and Alibaba Cloud training systems. Keywords: 智能陪练, 代理人培训, 保险训练, 产品陪练, 话术训练, 角色扮演, 技能评估, AIA培训, 平安培训, 代理人展业, 保险销售, 客户面谈, 异议处理, 保险培训系统, 学习路径.
As a process C 63/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
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") - warning
body-longSKILL.md body ≈ 5153 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "capabilities"
Process rating: all ten parameters 63/100
- 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 (Insurance Agent Intelligent Trainer) differs from the folder (insurance-agent-trainer)
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5153 tokens
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 16 steps
- 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)
- -237 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 593: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 16 items
- +3Output format is stated explicitly
- +4Has examples (18 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.