calendar-reminders

calendar-reminders is a skill for Claude Code, Codex from InternLM/WildClawBench. It costs 49 tokens per session (568 once invoked), scanned B, original, MIT.

A calendar and reminder workflow built around Google Calendar, with optional CalDAV calendars such as iCloud. It reads calendar data and produces a JSON plan for one-time reminders.

In plain words
What is it for?
Use it to read or manage Google Calendar events, optionally work with CalDAV calendars, and create reminder plans for OpenClaw.
Why use it?
It brings calendar events and reminder planning into command-line workflows instead of requiring manual checking and scheduling.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to read or manage Google Calendar events, optionally work with CalDAV calendars, and create reminder plans for OpenClaw.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/internlm/wildclawbench/calendar-reminders
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add InternLM/WildClawBench --skill calendar-reminders
Clone the repo
git clone --depth 1 https://github.com/InternLM/WildClawBench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for calendar-reminders

README.md
[![agentmods](https://agentmods.dev/badge/skills/internlm/wildclawbench/calendar-reminders.svg)](https://agentmods.dev/skills/internlm/wildclawbench/calendar-reminders)
Your own site
<a href="https://agentmods.dev/skills/internlm/wildclawbench/calendar-reminders"><img src="https://agentmods.dev/badge/skills/internlm/wildclawbench/calendar-reminders.svg" alt="Measured on agentmods" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 568 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high System Prompt Leakage · line 36
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00568
Opus 5 $0.00024 $0.00284
Sonnet 5 $0.00010 $0.00114
Haiku 4.5 $0.00005 $0.00057

Measured 8d ago against content hash 8580d9533af9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade B, and why

calendar-reminders scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/calendar_reminder_plan.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks the agent to reveal its instructionsmediumSystem prompt leakage

Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.

The wrapper uses `--noauth_local_server` to print instructions.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- The planner runs `gcalcli`/`khal` using `subprocess.check_output([...], shell=False)` (argument-list form; safe against shell injection from event titles).
skills/1/calendar-reminders/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

gcalcli calendar wrapper + reminder planner

This skill provides:

  • scripts/calendar — wrapper around gcalcli
  • scripts/calendar_reminder_plan.py — produces a JSON plan for reminder scheduling
  • references/openclaw-calendar.example.json — example config format

Config

Copy the example config to a private location and edit it:

  • Default path: ~/.config/openclaw/calendar.json
  • Override with env: OPENCLAW_CALENDAR_CONFIG=/path/to/calendar.json

Requirements

  • Required: python3, gcalcli
  • Optional (for CalDAV/iCloud): vdirsyncer, khal

Security notes (why ClawHub may flag this)

This skill invokes external binaries and is config-driven.

  • The planner runs gcalcli/khal using subprocess.check_output([...], shell=False) (argument-list form; safe against shell injection from event titles).
  • If you wire a cron job to run vdirsyncerSyncCommand, make sure you run it as an argv list (subprocess.run(cmd_list, shell=False)), not as a shell string.
  • Only point gcalcliPath / khalBin to trusted binaries (prefer absolute paths). Don’t run untrusted paths.

Auth (Google)

gcalcli requires OAuth. On headless servers you may need SSH port-forwarding. The wrapper uses --noauth_local_server to print instructions.

Reminder planning

The planner outputs a JSON blob describing reminders to schedule. A separate cron job (or an agent turn) can read it and create one-shot OpenClaw reminders.

Defaults:

  • Ignore birthdays.
  • Timed events are considered important.
  • All-day events only trigger reminders if their title matches configured keywords.

Wiring a daily reminder scheduler (OpenClaw)

Create a daily cron job (e.g. 00:05 local time) that:

  1. If CalDAV is enabled in config, runs the configured vdirsyncer sync command.
  2. Runs scripts/calendar_reminder_plan.py to get a JSON plan.
  3. For each planned reminder, creates a one-shot OpenClaw systemEvent reminder at reminderAtUtc.
  4. Writes a small state file so you don’t schedule duplicates.

Read the full file on GitHub · 58 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 58 lines · 0 tokens per session scan B 8580d9533af9

Subscribe to this mod's changes

calendar-reminders is a skill published in the GitHub repository InternLM/WildClawBench (516 stars, last pushed 22d ago), licensed MIT. It adds 49 tokens to every session and 568 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (asks the agent to reveal its instructions, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.