Agent skill

Task Reminder

by aipoch in aipoch/medical-research-skills

Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system…

MITAuto-check passedDocuments & Office

Install Task Reminder

skills CLI
$ npx skills add aipoch/medical-research-skills --skill task-reminder -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills task-reminder --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/scientific-skills/Other/task-reminder .claude/skills/task-reminder && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
task-reminder
GitHub stars
2k
Token cost
~1.8k tokens
SKILL.md length
786 words
Files
10 (incl. scripts)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system…

  • Works in 2 steps: Run with interactive input → Run with JSON input (recommended for…
  • Tasks that involve CSV and tabular files
  • SKILL.md covers Validation Shortcut, When to Use, Key Features and Dependencies, plus 11 more sections
  • Runs Python scripts from its folder; calls python

What it does

Task Reminder is an agent skill from aipoch/medical-research-skills. Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system notifications.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts (for example `input.json`, `input_deadline.json` and `input_next.json`).

It sits in Documents & Office, covering CSV and tabular files. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Tasks that involve CSV and tabular files

Example prompts

  • “/task-reminder”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Run with interactive input
  2. Run with JSON input (recommended for repeatable runs)

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Task Reminder loads about 1.8k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 786 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 786 words, ~1,778 tokens.

Download SKILL.mdSave it as .claude/skills/task-reminder/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
task-reminder
description
Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system notifications.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Validation Shortcut

Run this minimal command first to verify the supported execution path:

bash
python scripts/task_reminder.py --help

When to Use

  • You have a scattered set of tasks and need them consolidated into an actionable, prioritized list.
  • You want a daily plan that tells you what to focus on each day within a date range.
  • You want a weekly reminder plan (e.g., every Monday) to review upcoming work.
  • You need a deadline-driven plan that highlights tasks approaching due dates.
  • You need to export reminders to Markdown/CSV for sharing, collaboration, or importing into other tools.

Key Features

  • Converts a raw task list into an actionable plan across a specified date range.
  • Supports reminder modes: daily, weekly, deadline, or all (default).
  • Exports results to:
    • reminders.md (human-readable actionable list + plan)
    • reminders.csv (tabular plan for spreadsheets/tools)
  • Accepts interactive input or JSON input via CLI.
  • Optional system notifications (disabled by default; requires explicit activation in the script/parameters if supported).

Dependencies

  • Python 3.x (standard library only; no third-party packages)

Example Usage

1) Run with interactive input
bash
python scripts/task_reminder.py

Create input.json:

json
{
  "start_date": "2026-03-01",
  "end_date": "2026-03-10",
  "reminder_mode": "all",
  "weekly_day": 0,
  "tasks": [
    {
      "title": "Write lab report",
      "deadline": "2026-03-05",
      "priority": 3,
      "estimate_hours": 2,
      "tags": ["Course", "Lab"]
    },
    {
      "title": "Prepare slides for meeting",
      "deadline": "2026-03-08",
      "priority": 2,
      "estimate_hours": 1.5,
      "tags": ["Work"]
    }
  ]
}

Run:

bash
python scripts/task_reminder.py --json input.json

Expected outputs in the working directory:

  • reminders.md
  • reminders.csv

Implementation Details

Input Schema

Minimum required fields

  • tasks: array of task objects
  • start_date: string in YYYY-MM-DD
  • end_date: string in YYYY-MM-DD

Optional fields

  • reminder_mode: one of daily / weekly / deadline / all (default: all)
  • weekly_day: integer 0..6 where 0=Monday and 6=Sunday (default: 0)

Task object fields (recommended)

  • title (string): task name
  • deadline (string, YYYY-MM-DD): due date used for deadline-based reminders
  • priority (number/int): higher value indicates higher priority (as provided by the user)
  • estimate_hours (number): effort estimate used for planning context
  • tags (array of strings): categorization for filtering/grouping in outputs
Reminder Modes
  • daily: generates a day-by-day plan within [start_date, end_date].
  • weekly: generates reminders on the specified weekly_day within the date range.
  • deadline: emphasizes tasks by approaching deadlines within the date range.
  • all: produces combined outputs for daily/weekly/deadline views.
Output Files
  • reminders.md: includes an actionable task list and the generated reminder plan in Markdown format.
  • reminders.csv: includes a structured reminder plan table suitable for spreadsheets and imports.
Security/Operational Constraints
  • Runs as a local script with no network access.
  • Writes only to the output files it generates (e.g., reminders.md, reminders.csv) in the specified/working directory.
  • System notifications are not enabled by default and require explicit activation if implemented.

When Not to Use

  • Do not use this skill when the required source data, identifiers, files, or credentials are missing.
  • Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
  • Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

  • A clearly specified task goal aligned with the documented scope.
  • All required files, identifiers, parameters, or environment variables before execution.
  • Any domain constraints, formatting requirements, and expected output destination if applicable.
Show full SKILL.md (321 more words)Show less
  1. Validate the request against the skill boundary and confirm all required inputs are present.
  2. Select the documented execution path and prefer the simplest supported command or procedure.
  3. Produce the expected output using the documented file format, schema, or narrative structure.
  4. Run a final validation pass for completeness, consistency, and safety before returning the result.

Output Contract

  • Return a structured deliverable that is directly usable without reformatting.
  • If a file is produced, prefer a deterministic output name such as task_reminder_result.md unless the skill documentation defines a better convention.
  • Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.

Validation and Safety Rules

  • Validate required inputs before execution and stop early when mandatory fields or files are missing.
  • Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
  • Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
  • Keep the output safe, reproducible, and within the documented scope at all times.

Failure Handling

  • If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
  • If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
  • If partial output is returned, label it clearly and identify which checks could not be completed.

Quick Validation

Run this minimal verification path before full execution when possible:

bash
python scripts/task_reminder.py --help

Expected output format:

text
Result file: task_reminder_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any

Deterministic Output Rules

  • Use the same section order for every supported request of this skill.
  • Keep output field names stable and do not rename documented keys across examples.
  • If a value is unavailable, emit an explicit placeholder instead of omitting the field.

Completion Checklist

  • Confirm all required inputs were present and valid.
  • Confirm the supported execution path completed without unresolved errors.
  • Confirm the final deliverable matches the documented format exactly.
  • Confirm assumptions, limitations, and warnings are surfaced explicitly.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts) in scientific-skills/Other/task-reminder of aipoch/medical-research-skills.

  • SKILL.md
  • input.json
  • input_deadline.json
  • input_next.json
  • input_weekly.json
  • reminders.csv
  • reminders.md
  • scripts/task_reminder.py
  • scripts/validate_skill.py
  • task-reminder_audit_result_v2.json

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Task Reminder next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Cliare Artifact Reviewmodiqo/cliare469—~2.4kAutomated safety check: PassApache-2.0
Convert Fileduckdb/duckdb-skills5991 repos~720Automated safety check: NotesMIT
Research Integrity Auditxuzhougeng/wisp-science1k—~2.6kAutomated safety check: PassAGPL-3.0

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Questions about Task Reminder

What does Task Reminder do?

Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system…. Task Reminder is an agent skill from aipoch/medical-research-skills. Organize scattered tasks into actionable lists and generate daily/weekly/deadline reminder plans when you need a structured schedule and exportable outputs (MD/CSV), with optional system notifications.

When should I use Task Reminder?

Task Reminder fits situations like: tasks that involve CSV and tabular files.

How do I install Task Reminder in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill task-reminder -a claude-code`. Or copy the skill folder (scientific-skills/Other/task-reminder in aipoch/medical-research-skills) into .claude/skills/task-reminder in your project. Claude Code loads it when a task matches its description.

How do I install Task Reminder in Codex?

Run `npx skills add aipoch/medical-research-skills --skill task-reminder -a codex`. Or copy the skill folder (scientific-skills/Other/task-reminder in aipoch/medical-research-skills) into .agents/skills/task-reminder in your project. Codex loads it when a task matches its description.

Can I use Task Reminder in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill task-reminder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/task-reminder, .gemini/skills/task-reminder, .github/skills/task-reminder and .opencode/skills/task-reminder in your project.

What does Task Reminder need to run?

Going by SKILL.md and its folder, Task Reminder needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Task Reminder access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Task Reminder safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Task Reminder use?

Task Reminder is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Task Reminder use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Task Reminder?

Skills that share tags, products or a category with Task Reminder: Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Sector Analyst (tradermonty/claude-trading-skills, 3k stars), Cliare Artifact Review (modiqo/cliare, 469 stars) and Convert File (duckdb/duckdb-skills, 599 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Task Reminder?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,973 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.