BD macmini-knowledge-base
⚠️ **本 skill 包含以下高危能力，使用前请仔细阅读 SKILL.md 顶部「⚠️ CAPABILITIES & RISKS」章节**： - Shell 执行 + 文件读写 + 安装 Homebrew 包（版本固定）+ 下载 Ollama 模型 - 修改 OpenClaw 配置 + 注册持久 cron 任务 + 飞书 webhook 推送 在 Mac Mini (M4) 上快速搭建本地知识库 + RAG 自然语言搜索系统。 适用场景： - 新 Mac 配置知识库：从零开始安装配置 Ollama、embedding模型、定时任务、文档解析 - 遇到 PDF 提取乱码、定时任务超时、skill 加载失败等问题 - 想要建立每日自动分析文档 + 08:00发送摘要到飞书的流程 - 迁移或复现知识库：打包整个 knowledge 目录和配置到新电脑 - **v1.4 新增**：CMap 残缺度自检（不预设来源）+ 50万字完整提取 + OCR fallback 到 .doc 本 skill 会引导完成：目录结构创建、依赖安装、脚本部署、定时任务注册、OpenClaw 配置。 ⚠️ **重要：能力范围** 本 skill 不只是「搭建」，还包含： - 批量 OCR 修复（扫描 summaries/archives 找乱码 + 重新提取） - 目录归档清理（移动重复/孤儿文件到 .trash/） - 自动定时任务（23:00 分析 + 06:00 飞书推送） 使用前请仔细评估批量修改风险。
As a process D 48/100 · 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: 9. 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 48/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3530 tokens
- 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 656: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (18 code blocks)
- +3All 5 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.