AC pans-discovery-playbook
AI算力销售发现阶段话术与框架工具。根据沟通场景（首次电话/需求介绍/POC/ 续约增购）和行业（科技/金融/医疗/自动驾驶/内容/制造/学术/政府） 自动生成访谈问题清单、行业背景知识、话术建议和异议处理策略， 输出 Markdown 或 JSON 格式发现指南。 触发词：发现阶段, 客户访谈, 话术指南, 异议处理, 需求挖掘, discovery, 首次沟通, 客户沟通, 销售话术
As a process C 53/100 · Has gaps — 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.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription 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. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 220 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 195: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: clean
This skill is a local AI compute sales playbook generator, with only a minor risk of activating too broadly.
LLM: benign (high) · VirusTotal: · 29 May 2026