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BC mac-reminders-agent

Integrate with macOS Reminders app to check, add, edit, delete, and complete reminders. Supports native recurrence (매주/weekly/毎週/每周) via Swift EventKit - creates single reminder with repeat rule. Supports editing and deleting reminders by ID (calendarItemIdentifier from EventKit). Supports multiple languages (en, ko, ja, zh) for trigger detection and response formatting. When users request recurring reminders, MUST use --repeat option (daily|weekly|monthly|yearly).

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 9 files body ≈ 2 320 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Integrate with macOS Reminders app to check, add, edit, delete, and complete reminders.

As a process C 62/100 · Has gaps — weak spots: when it triggers, running it twice, progress reporting

IntegrationAI and agentsWriting and documentsPersonal 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
B
80/100
safety, quality, tests
Safety 60%
76
Quality 40%
86
Run on models
none yet
Process rating
C
62/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
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.
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 · 3

  • high Dangerous commands cmd-persistence README.md:328
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    launchctl load ~/Library/LaunchAgents/com.reminders.daily.plist
Medium and low: 2
  • medium Dangerous commands cmd-persistence README.md:294
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (quoted — discussed, not commanded)
    Create `~/Library/LaunchAgents/com.reminders.daily.plist`:
    quoted
  • low Dangerous commands cmd-cron-mention README.md:263
    Mentions editing / listing crontab
    crontab -e

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • note frontmatter-key unknown frontmatter key "requirements"
  • note frontmatter-key unknown frontmatter key "install"

Process rating: all ten parameters 62/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 79 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2320 tokens
  • low 12 top-level sections: this looks like several domains in one skill
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +2Single-language instructions
  • +3Description length 469: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 79 items
  • +3Output format is stated explicitly
  • +4Has examples (12 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.