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DD weekly-report-generator

周报生成器是一款基于 AI 的智能周报自动化工具，能够从本地 Git 提交记录、工作描述、工作截图中自动提取信息， 生成指定时间（默认本周）的高质量、模块化、业务化的周报文档，并自动发送到飞书（可设置定时发送）。 彻底解放双手，让写周报从"痛苦的回忆作业"变成"一句话的事"。 核心亮点： 1. 一键生成：一句"按照skill帮我生成周报"，剩下的全部自动完成 2. 零配置使用：无需手动统计代码、无需对接gitlab/github地址、无需整理提交记录、直接扫描本地所有文件夹 3. 智能发送：生成后自动推送到飞书，无需手动操作 主要功能： • 自动读取指定时间范围的 git 提交记录，智能分类工作内容（功能开发、Bug修复、优化等） • 支持多项目、多分支统计，生成格式化的 Markdown 周报文档 • 可自定义时间范围和格式模板，灵活适配不同团队需求

Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: memorial v1.0.2 MIT-0 6 files · 2 scripts body ≈ 1 335 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorGitHubGitLabSoftware developmentData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
D
44/100
safety, quality, tests
Safety 60%
23
Quality 40%
76
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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 · 5

  • high Dangerous commands cmd-persistence 安装和配置指南.md:112
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    cp scripts/com.user.weekly-report.plist ~/Library/LaunchAgents/
  • high Dangerous commands cmd-persistence 安装和配置指南.md:141
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load ~/Library/LaunchAgents/com.user.weekly-report.plist
  • high Dangerous commands cmd-persistence 安装和配置指南.md:151
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl unload ~/Library/LaunchAgents/com.user.weekly-report.plist
  • high Dangerous commands cmd-persistence 安装和配置指南.md:154
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl unload ~/Library/LaunchAgents/com.user.weekly-report.plist
Medium and low: 1
  • medium Dangerous commands cmd-persistence 安装和配置指南.md:119
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (quoted — discussed, not commanded)
    编辑 `~/Library/LaunchAgents/com.user.weekly-report.plist`：
    quoted

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description 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
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (weekly-report-generator) differs from the folder (weekly-report-generator-feishu)
  • 100Tools and files. No external tools needed
  • 100Steps. 74 steps
  • 100Execution cost. Instruction body is 1335 tokens
  • 100Progress reporting. Reports progress

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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 383: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 74 items
  • +4Has examples (10 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This skill does what it says, but it can broadly scan local work history and send the resulting report to Feishu automatically without a clear review step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026