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Stay Within Limits

OrganizationPopular
BuilderIO
stay-within-limits

Use when long-running or parallel agent work must respect 5-hour and weekly usage limits by checking usage between waves, pausing near the cap, and resuming only when the window is clear.

Overview

PublisherBuilderIO
Repositoryskills
Skill namestay-within-limits
Stars
4.3K
Forks
211
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by BuilderIO on GitHub. Read the source before you install it.

Installation

Install the Stay Within Limits AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/BuilderIO/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/stay-within-limits .claude/skills/stay-within-limits
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Stay Within Limits in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Stay Within Limits on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Stay Within Limits is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Stay Within Limits

Keep long-running agent work inside the current 5-hour and weekly usage windows. Check usage before launching substantial work and between waves of parallel subagents. If an active 5-hour or weekly limit is at or above 95%, pause new work until the window is clear enough to continue safely.

Core Loop

  1. Run a bounded wave of work. Default to at most 3 parallel subagents unless the user or host gives a different throttle.
  2. Wait for the wave to finish. Do not interrupt in-flight subagents just to save budget; that usually loses work.
  3. Check current 5-hour and weekly usage with the host's usage/budget tool.
  4. If either window is at or above 95%, stop launching work and schedule a self-contained resume when the relevant window should clear.
  5. On resume, re-check the real window or block before continuing. Do not trust elapsed wall-clock time alone.

Usage Signals

Prefer a first-party host usage tool when available. In Claude Code, use:

sh
npx -y ccusage@latest blocks --active --json

Use the JSON to identify the active block start, current cost or percentage, and time remaining. On wake, compare the active block start timestamp with the previous one; a new timestamp is stronger evidence than "enough time passed."

If the tool reports cost instead of a direct percentage, convert through the current account limit when known. For Claude Max-style 5-hour blocks, some users prefer an earlier caution threshold around $500-550; treat that as a user-configured guardrail, not a universal rule. The default stop rule is still 95% of the active 5-hour or weekly limit.

Pausing And Resuming

When a wake/resume tool is available, schedule a wakeup for:

txt
min(3600, secondsUntilWindowClears)

If the runtime clamps wake delays to 60-3600 seconds, chain wakeups for longer waits. Each wakeup should re-check usage, reschedule if still over budget, and continue only when the window is safely below the threshold.

Make wake prompts self-contained. Include:

  • The remaining plan.
  • The check-then-reschedule rule.
  • The 95% threshold and wave throttle.
  • The exact usage command or host usage tool to run.
  • The previous block/window identifier when available.
  • The next verification steps.
  • The next wave's handoff packets, including scope, verification commands, and stop conditions, if delegation will resume.

Choosing The Wait Mechanism

  • Use a wake/resume tool when the agent needs instructions attached to the future resume.
  • Use a background sleep or watcher for fixed timers and things a process can observe directly.
  • Use cron or recurring schedules only for recurring fresh-session work.

Avoid short-interval polling for things the host will notify you about, such as background task or subagent completion. For budget pauses, a prompt-cache miss after a long sleep is acceptable; preserving the limit matters more.

Reporting

If you pause, tell the user which window is over threshold, the observed usage, when you scheduled or expect the next check, and what work remains. Keep enough state in the wake prompt that the next turn can resume without relying on conversation momentum.

Frequently asked questions

What does the Stay Within Limits AI skill do?

Use when long-running or parallel agent work must respect 5-hour and weekly usage limits by checking usage between waves, pausing near the cap, and resuming only when the window is clear.

Why use Stay Within Limits on TypingMind?

Because you install it once and use it with any model. Stay Within Limits is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Stay Within Limits in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BuilderIO/skills/tree/main/skills/stay-within-limits. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Stay Within Limits?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Stay Within Limits?

As many as you like. As long as a model supports skills, you can use Stay Within Limits with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Stay Within Limits AI skill free?

Yes. It is published on GitHub by BuilderIO under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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