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AB moltbot-plugin-2do

Create tasks and send them to 2Do app via email. Use when the user wants to: (1) add, create, or record a task/todo/reminder in any form - e.g. '添加任务', '创建待办', '新建任务', '加个任务', '记录任务', 'add task', 'create todo'; (2) ask to be reminded of something - e.g. '提醒我', '别忘了', '记得', '帮我记一下', 'remind me', 'remember to'; (3) mention something they need to do and want it tracked - e.g. '明天要开会', '周五前交报告', '下午去买菜'; (4) want to add items to a todo list or task manager - e.g. '加到待办', '放到任务列表', '记到清单里'; (5) describe a task with list/tag organization - e.g. '添加到工作列表', '标签是紧急'; (6) mention urgency or importance - e.g. '紧急', '重要', 'urgent', 'important'. Parses natural language (Chinese and English) to extract task title, due date/time, priority, optional list name, and optional tags, then sends a formatted email to the user's configured 2Do inbox.

modbender/skill-library-mcp Agent Skills author: modbender MIT 18 files · 1 script body ≈ 548 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Create tasks and send them to 2Do app via email.

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

GeneratorPersonal productivitytype 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
A
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
82
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:37
      High-entropy token-like string (may be an id, hash or a credential)
      resolution: {integrity: sha512-GZMB+a0mO…4cw+w1WV…UED+1X8a…sJi+8mgpw==}
    • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:97
      High-entropy token-like string (may be an id, hash or a credential)
      resolution: {integrity: sha5…HK5+NE/tvnRLbIqUWa+0E9N4WNMjmp/kXXP…R8w==}
    • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:175
      High-entropy token-like string (may be an id, hash or a credential)
      resolution: {integrity: sha5…78O/B3Kkh+nKABUF++bvJv…56W+C8F9…X6m+IktJnIb1Jjg==}
    • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:236
      High-entropy token-like string (may be an id, hash or a credential)
      resolution: {integrity: sha5…zN3+kuBL…KQ8+XS6hp9nY7B+ZeK0…Haw==}
    • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:242
      High-entropy token-like string (may be an id, hash or a credential)
      resolution: {integrity: sha5…j98+PZe/AXaG…EeK+Mrp9…mrw==}

    Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 65/100

    • 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
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 6 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 548 tokens

    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)
    • +3Description length 838: 120–800 characters recommended
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 6 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.