BD getnote-knowledge-master
Get笔记 · 六步抄作业版。复刻 AI 大神卡帕西的知识管理方法论，融合 Get笔记 API + @getnote/cli 实现一键式六步知识管理流程。 **何时激活：** (1) 用户提到"六步抄作业"、"卡帕西知识管理"、"知识库抄作业" (2) 用户要执行完整知识管理流程（建库→存入→整理→搜索→反哺→体检） (3) 用户一句话触发多步骤知识管理操作，如"帮我把最近AI进展整理一下存到知识库" (4) 用户提到"Get笔记升级版"、"知识沉淀"、"知识复利" (5) 常规 Get笔记 操作（保存/搜索/知识库/标签）但带有工作流意味（批量、自动化、定期） **默认主阵地："得到"知识库（topic_id: `eYzMmvnm`）** 张公子的主要工作环境在此知识库，六步法的所有操作默认以此为上下文，除非用户明确指定其他知识库。 本 Skill 基于 Get笔记 API + @getnote/cli，通过 orchestrated 多步骤流程实现六步法。
As a process D 43/100 · 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: 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 43/100
- 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
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1487 tokens
- low 14 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (6 tags): a typed call is more reliable
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 439: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (22 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.