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Blast Radius

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cursor
blast-radius

Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you don't trust.

Overview

Publishercursor
Repositoryplugins
Skill nameblast-radius
Stars
8K
Forks
728
Bundled files
Instructions only
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 cursor on GitHub. Read the source before you install it.

Installation

Install the Blast Radius 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/cursor/plugins.git /tmp/plugins
mkdir -p .claude/skills
cp -r /tmp/plugins/pstack/skills/blast-radius .claude/skills/blast-radius
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blast Radius 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 Blast Radius 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 Blast Radius 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.

Blast radius

Find what a change breaks somewhere else, before it ships. Use for "blast radius of X", "what could this break", or reviewing a small diff you don't trust yet.

Companion to how and why. how tells you what the code does. why tells you why it's shaped that way. Blast radius tells you what it breaks somewhere else.

Listing the callers is not the job. The agent can grep those in a second. The job is the breakage grep won't show you.

Don't trust your own writeup

A blast-radius writeup that sounds right is worthless. It reads as convincing whether or not it's true. So don't hand back the writeup. Find the one or two facts the whole thing depends on and prove them by running code.

How sure are you

For each fact the change's safety depends on, get it as far down this list as is cheap, and say where it stopped.

  1. You said so. Worthless on its own.
  2. You pointed at the line. A real file:line, or the library's own source.
  3. You showed the bad case can't happen. You walked the failure step by step and it doesn't reach.
  4. You ran it. A script or test that calls the real code and fails loud if you're wrong.
  5. You reproduced it in the running app.

Any safety fact you can't get to step 4, say so. Don't write it up as settled. Step 4 is usually one small script that imports the same library the app ships and calls the exact function you're worried about.

Steps

  1. Read the change. The diff, the symbols it adds, changes, and deletes, and what it now does differently, including the part the diff doesn't spell out. Use why step 2 to pull the PR and commits.
  2. Find the one fact it's safe because of. Most changes that look risky are safe because of a single fact, like "this call only drops already-dead cache entries and does nothing else". Find that fact. If it holds, most risky cases are cleared at once. Spend your time here, not on a long list of maybes.
  3. Look where grep stops. Read the source of the library you call, and check its pinned version and any local patch. Work out when things run: microtasks, unmount and teardown, Solid versus React. Follow what a symbol search misses: the JSON an API returns, a DB column, a wire format, another language reading the same bytes, a feature flag, code three hops downstream.
  4. Be honest about each risk. Give it a real chance of happening and a real cost if it does. Keep the risks you confirmed. List the ones you checked and cleared separately. Same rules as why. Cite a real file:line, a search that finds nothing is still an answer, and never make up a caller or an API.
  5. Prove the one fact. Write a script or test that runs the real code, run it, and paste what happened. If you can't prove it cheaply, mark it unproven. Don't overstate.
  6. For a big or wide change, run it as an arena. Ask several models the same question and merge the answers. Different models catch different real bugs.

What to hand back

  • What it does. What changed, including the part that isn't obvious.
  • The one fact it's safe because of. State it, say which step you got it to, and show the proof. If you couldn't prove it, write unproven.
  • Risks. Only the real ones. Each names how it breaks, the file:line, how likely and how bad, and how to check. Paste the proof for the ones that matter.
  • Cleared. What you checked and why it's fine.
  • Before you merge. The cheapest test or repro that catches the real bug, including the script you wrote.

Write it through unslop, cite real code, and strip anything private before it goes anywhere public.

Reply: the writeup above, with the one safety fact either proven or marked unproven.

Frequently asked questions

What does the Blast Radius AI skill do?

Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you don't trust.

Why use Blast Radius on TypingMind?

Because you install it once and use it with any model. Blast Radius 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 Blast Radius in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cursor/plugins/tree/main/pstack/skills/blast-radius. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Blast Radius?

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 Blast Radius?

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

Is the Blast Radius AI skill free?

It is published on GitHub by cursor. Check the repository for licensing terms. 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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