BD skillhub-daily
SkillHub Daily — 与 ClawHub Daily（口碑精品/趋势洞察）互补的每日推荐引擎。 本技能的行为范围（用户须知）： - 读取本地记忆文件（TRAE memory 目录）提取关键词用于个性化推荐，仅使用关键词匹配，不传输原始记忆内容 - 调用 skillhub CLI 获取 SkillHub.cn 排行榜和搜索数据（网络请求） - 调用 skillhub skill evaluation/reports 获取深度评估（网络请求，可选） - 将推荐简报写入本地文件和外部服务（Obsidian/IMA/飞书），需用户配置对应凭证 - 推荐结果中不包含原始记忆内容，仅记录关键词匹配数量 差异化特色： - 国内优先：重点推荐适配国内生态的技能（飞书/微信/钉钉/小红书/抖音等） - 活跃开发者：发现高产开发者及其代表作，追踪值得关注的技能作者 - 双实验室安全审计：调用 skillhub skill reports 获取安全评估 - AI 6维质量评估：调用 skillhub skill evaluation 获取可用性/安全性/文档等评分 - 3级权重记忆碰撞：project_memory×3 / topics×2 / user_profile×1 数据源：SkillHub.cn API（via skillhub CLI，结构化 JSON，0 token 消耗） 扫描规模：7 排行榜 × 100 + 11 分类 × 20 搜索 + 6 关键词 × 20 搜索 ≈ 1000+ 候选 推荐维度：趋势飙升 / 新星上线 / 国内优先 / 活跃开发者 / 记忆碰撞 / 痛点匹配 / 官方认证 去重机制：7 天跨维度去重 三处存放：Obsidian inbox / IMA FIM 知识库 / 飞书云文档 权限声明：需要网络访问（skillhub CLI）、本地文件读写（data 目录）、环境变量（IMA_OPENAPI_CLIENTID/IMA_OPENAPI_APIKEY/OBSIDIAN_VAULT_PATH/TRAE_MEMORY_PATH） 触发场景： - 用户希望每日收到 SkillHub 国内技能推荐 - 用户希望发现适配国内的 AI 技能 - 用户希望追踪活跃开发者 - 用户说"SkillHub 日报"、"国内技能推荐"、"有什么新 Skill" Do NOT use for ClawHub 平台推荐（用 clawhub-daily）、通用代码开发、非 Skill 项目。
SkillHub Daily — 与 ClawHub Daily（口碑精品/趋势洞察）互补的每日推荐引擎。 本技能的行为范围（用户须知）： - 读取本地记忆文件（TRAE memory 目录）提取关键词用于个性化推荐，仅使用关键词匹配，不传输原始记忆内容 - 调用 skillhub CLI 获取…
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Shorten the description to 1024 characters.
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1071 chars, limit 1024 - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary"
Process rating: all ten parameters 47/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1143 tokens
- low 11 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
- +3Description length 1070: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +4Description says when NOT to use the skill
- +4Structure: 26 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (3 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.