Agent skill

Co Tank Monitor

by aipoch in aipoch/medical-research-skills

IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities.

MITAuto-check passedProductivity & Automation

Install Co Tank Monitor

skills CLI
$ npx skills add aipoch/medical-research-skills --skill co-tank-monitor -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills co-tank-monitor --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/co2-tank-monitor .claude/skills/co-tank-monitor && 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
co-tank-monitor
GitHub stars
1.9k
Token cost
~1.8k tokens
SKILL.md length
671 words
Files
3 (incl. scripts)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities.

  • Works in 5 steps: Depletion Prediction → Weekend Risk Detection → Status Levels → …
  • Tasks that involve Incident response
  • SKILL.md covers Input Validation, Quick Check, Workflow and Core Capabilities, plus 7 more sections
  • Runs Python scripts from its folder; calls python

What it does

Co Tank Monitor is an agent skill from aipoch/medical-research-skills. IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities. Monitors cylinder pressure, calculates consumption rates, provides early warnings, and supports automated scheduling via cron.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `co2-tank-monitor_audit_result_v2.json` and `scripts/main.py`).

It sits in Productivity & Automation, covering Incident response and Scheduled and recurring tasks. 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 Incident response
  • Tasks that involve Scheduled and recurring tasks

Example prompts

  • “/co-tank-monitor”

Requirements

  • Python 3

Workflow steps

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

  1. Depletion Prediction
  2. Weekend Risk Detection
  3. Status Levels
  4. Cylinder Specifications
  5. Automated Scheduling

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 1 file 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

    Links to these hosts (documentation or services it may open):

    • thermofisher.com
    • osha.gov

    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

Co Tank Monitor loads about 1.8k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 671 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
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). 671 words, ~1,755 tokens.

Download SKILL.mdSave it as .claude/skills/co-tank-monitor/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
co-tank-monitor
description
IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities. Monitors cylinder pressure, calculates consumption rates, provides early warnings, and supports automated scheduling via cron.
license
MIT
author
AIPOCH

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

CO2 Tank Monitor

Monitor CO2 cylinder pressure and predict depletion times to prevent gas outages in cell culture incubators, particularly during weekends when laboratories are unmanned.

Key Capabilities:

  • Pressure-Based Depletion Prediction: Calculate remaining cylinder life
  • Weekend Risk Detection: Identify depletion during unmanned periods
  • Multi-Cylinder Support: Handle 10L and 40L cylinder sizes
  • Automated Alert System: Color-coded status with actionable recommendations
  • Simulation Mode: Test monitoring scenarios for staff training

Input Validation

This skill accepts: current cylinder pressure (MPa), daily consumption rate (MPa/day), cylinder capacity (10 or 40 L), and optional alert threshold (days).

If the request does not involve monitoring CO2 cylinder pressure or predicting depletion — for example, asking to monitor other gases, control incubator temperature, or manage lab inventory — do not proceed. Instead respond:

"CO2 Tank Monitor is designed to predict CO2 cylinder depletion and detect weekend risk for cell culture facilities. Please provide current pressure and daily consumption rate. For other lab monitoring tasks, use a more appropriate tool."


Quick Check

bash
python -m py_compile scripts/main.py
python scripts/main.py --help

Workflow

  1. Confirm current pressure, daily consumption rate, cylinder capacity, and alert threshold.
  2. Unit detection: If pressure > 15 and < 220, assume PSI and auto-convert (MPa = PSI × 0.0069). If pressure > 15 and < 150, assume Bar and auto-convert (MPa = Bar × 0.1). State the unit assumption explicitly in the output.
  3. Validate that inputs are within plausible ranges (pressure 0–15 MPa after conversion, consumption 0.1–5 MPa/day).
  4. Run the script or apply the documented calculation path with only the inputs available.
  5. Return a structured result separating assumptions, deliverables, risks, and unresolved items.
  6. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Fallback: If pressure is not provided, respond: "Required parameter --pressure not provided. Please supply current cylinder pressure in MPa. Use --simulate to generate a training scenario without real data."


Core Capabilities

1. Depletion Prediction
python
from scripts.main import calculate_remaining_days, calculate_depletion_time
remaining_days = calculate_remaining_days(pressure=8.0, daily_consumption=1.5)
depletion_time = calculate_depletion_time(remaining_days)
# Formula: remaining_days = pressure / daily_consumption
2. Weekend Risk Detection
python
from scripts.main import is_weekend, will_deplete_on_weekend
weekend_risk = will_deplete_on_weekend(depletion_time, alert_days=2)

Weekend Risk Scenarios:

ScenarioRisk LevelAction Required
Depletion Saturday/Sunday🔴 HighImmediate replacement or weekend duty
Depletion Monday morning🟡 MediumReplace Friday afternoon
Depletion mid-week🟢 LowSchedule routine replacement
3. Status Levels
CodeStatusConditionAction
0🟢 NormalDays > alert_days + 2No action needed
1🟡 CautionDays within alert_days + 2Monitor closely
2🔴 DangerDays ≤ alert_days or weekend riskReplace immediately
4. Cylinder Specifications
CapacityFull PressureDuration (@1.5 MPa/day)
10L~15 MPa~10 days
40L~15 MPa~40 days
5. Automated Scheduling
bash
# Daily check at 9:00 AM (cron)
0 9 * * * cd /lab/scripts && python scripts/main.py --pressure $(cat sensor.log | tail -1) --quiet

# Pre-weekend check (Friday 5 PM)
0 17 * * 5 cd /lab/scripts && python scripts/main.py --pressure $(cat sensor.log | tail -1)

CLI Usage

text
# Manual morning check
python scripts/main.py --pressure 8.5 --daily-consumption 1.2

# Pre-weekend check with extended alert
python scripts/main.py --pressure 5.5 --alert-days 3

# Simulation for training
python scripts/main.py --simulate

Show full SKILL.md (274 more words)Show less

Parameters

ParameterTypeRequiredDescription
--pressurefloatNoCurrent cylinder pressure in MPa
--capacityintNoCylinder capacity (10 or 40 L)
--daily-consumptionfloatNoAverage daily consumption (MPa/day)
--alert-daysintNoAlert threshold in days (default 2)
--simulateflagNoGenerate random training scenario
--quietflagNoSuppress verbose output (for cron)

Output Requirements

Every final response must make these explicit:

  • Objective or requested deliverable
  • Inputs used (pressure, consumption, capacity) and assumptions introduced (including unit conversion if applied)
  • Calculation method applied
  • Core result: remaining days, depletion datetime, weekend risk status, recommendations
  • Constraints: Prediction assumes constant consumption rate. Actual depletion may vary with temperature, usage patterns, and weekend vs. weekday consumption.
  • Unresolved items and next-step checks

Error Handling

  • If pressure is not provided, offer simulation mode or request the value explicitly.
  • If values are outside plausible ranges (pressure >15 MPa or <0), flag as implausible.
  • If scripts/main.py fails, report the failure point and provide manual calculation fallback using the formula above.
  • Do not fabricate pressure readings or depletion predictions.

Common Pitfalls

  • Inconsistent reading times: Take readings at same time daily (e.g., 9:00 AM ± 30 min)
  • Wrong consumption estimates: Calculate from actual usage over 2+ weeks
  • Pressure unit confusion: Standardize on MPa; convert if gauge shows PSI or Bar
  • Alert fatigue: Batch daily reports; only escalate urgent alerts immediately
  • Wrong cylinder capacity: 10L vs 40L confusion causes 4× prediction error

Pressure Conversion Reference

UnitMPaPSIBar
MPa1.0145.010.0
PSI0.00691.00.069
Bar0.114.51.0

Typical Cylinder Pressures: Full ~15 MPa | Working 8–10 MPa | Replace threshold 3–5 MPa | Empty <1 MPa


References

© 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 2 other files (scripts) in scientific-skills/Other/co2-tank-monitor of aipoch/medical-research-skills.

  • SKILL.md
  • co2-tank-monitor_audit_result_v2.json
  • scripts/main.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

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Questions about Co Tank Monitor

What does Co Tank Monitor do?

IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities. Co Tank Monitor is an agent skill from aipoch/medical-research-skills. IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities.

When should I use Co Tank Monitor?

Co Tank Monitor fits situations like: tasks that involve Incident response; tasks that involve Scheduled and recurring tasks.

How do I install Co Tank Monitor in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill co-tank-monitor -a claude-code`. Or copy the skill folder (scientific-skills/Other/co2-tank-monitor in aipoch/medical-research-skills) into .claude/skills/co-tank-monitor in your project. Claude Code loads it when a task matches its description.

How do I install Co Tank Monitor in Codex?

Run `npx skills add aipoch/medical-research-skills --skill co-tank-monitor -a codex`. Or copy the skill folder (scientific-skills/Other/co2-tank-monitor in aipoch/medical-research-skills) into .agents/skills/co-tank-monitor in your project. Codex loads it when a task matches its description.

Can I use Co Tank Monitor 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 co-tank-monitor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/co-tank-monitor, .gemini/skills/co-tank-monitor, .github/skills/co-tank-monitor and .opencode/skills/co-tank-monitor in your project.

What does Co Tank Monitor need to run?

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

Does Co Tank Monitor access the network?

SKILL.md names 2 domains. As links in the text: thermofisher.com and osha.gov. This is read from the text; nothing was executed.

Is Co Tank Monitor 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 Co Tank Monitor use?

Co Tank Monitor 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 Co Tank Monitor use?

About 1.8k tokens (SKILL.md is roughly 7k 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 Co Tank Monitor?

Skills that share tags, products or a category with Co Tank Monitor: Hunting For Persistence Mechanisms In Windows (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Hunting For Scheduled Task Persistence (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Analyzing Linux System Artifacts (mukul975/Anthropic-Cybersecurity-Skills, 34k stars) and Cronalytics (8bit64k/cronalytics, 112 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Co Tank Monitor?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,937 GitHub stars. The repository holds 578 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.