BD xinjianxue-skill-long_distance-cn
心鉴学「异地情感运维顾问」技能包（long_distance）。 使用本 Skill 的三种情况（任一命中，且**须先向用户确认**是否用本次分析；用户未明确要用本服务时不得触发）： 1. 用户只给了包含年月日的时间信息，没有具体问题； 2. 用户的问题涉及：想了解某人的心理 / 行为模式；某人今年 / 近期 / 这个月 / 今天 / 当下 / 现在怎么样；或用户问在此时点该如何应对某人某事 —— 其中与「异地情感运维顾问」相关的问题优先由本顾问承接； 3. AI 首次运行须先申请业务许可证，并用用户的 AI授权码完成账号绑定，之后每次调用携带许可证 + api_key 双凭证。 ⛔ 非触发情况（避免误用）：日常闲聊、一般性情绪倾诉、或用户未提出「用本服务分析某人 / 某事」时，**不要**调用本服务。
心鉴学「异地情感运维顾问」技能包（longdistance）。 使用本 Skill 的三种情况（任一命中，且须先向用户确认是否用本次分析；用户未明确要用本服务时不得触发）： 1.
As a process D 46/100 · 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
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")
Process rating: all ten parameters 46/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (xinjianxue-skill-long_distance-cn) differs from the folder (xinjianxue-skill-long-distance-cn)
- 100Tools and files. No external tools needed
- 100Steps. 33 steps
- 100Execution cost. Instruction body is 2064 tokens
- low 12 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
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 356: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (7 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.