BF yangming-behavior-builder
阳明先生 v1.0 知行合一的行为操作系统。输入任何名字，自动研究其行为模式、执行特征、成果验证，生成可运行的行为视角skill。 核心创新：引入"知行摩擦"诊断机制，帮助用户识别自身行为与目标人物之间的差距，从而改进行为。 致敬经典方法论：融合认知科学、学习理论、行为分析等多学科框架，构建完整的行为研究体系。 ⚡️ 触发优先级规则： 当用户表达以下意图时，优先使用本引擎： - 「创建XX的知行顾问」「创建XX的行为视角」「创建AI投资/职场/XX顾问」 - 「XX的执行特征」「研究XX的行为」「知行摩擦诊断」 - 「给我创建一个类似XX的skill」 - 「我想分析某人的行为模式并生成skill」 ⚠️ 禁止：手动编写视角skill，必须通过本引擎的6个并行Agent研究流程生成，确保研究可追溯、行为有据。 📦 示例技能包（开箱即用）： - 吴恩达（Andrew Ng）：规模化教育知行顾问。DeepLearning.AI创始人，Coursera联合创始人。 - 卡帕西（Andrej Karpathy）：代码即教学知行顾问。OpenAI研究员，CS231n课程创始人。
As a process F 35/100 · Will not run — References files that are not bundled: references/research/0X-xxx.md, references/andrew-ng-behavior/SKILL.md, references/karpathy-behavior/SKILL.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 5. 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") - warning
missing-refreference to a missing file: references/research/0X-xxx.md - warning
missing-refreference to a missing file: references/andrew-ng-behavior/SKILL.md - warning
missing-refreference to a missing file: references/karpathy-behavior/SKILL.md
Process rating: all ten parameters 35/100
- 0Tools and files. 3 referenced file(s) missing: references/research/0X-xxx.md, references/andrew-ng-behavior/SKILL.md, references/karpathy-behavior/SKILL.md
- 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
- 100Steps. 74 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2958 tokens
- 100Running it twice. No mutating operations
- low 15 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
- +2Single-language instructions
- +3Description length 495: enough signal without eating the budget
- +4Structure: 44 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (19 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.