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.
npx skills add J-StaR-Films-Studios/VibeCode-Protocol-Suite --skill blast-radiusgit clone --depth 1 https://github.com/J-StaR-Films-Studios/VibeCode-Protocol-SuiteWrote 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.
[](https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/blast-radius)<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/blast-radius"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/blast-radius/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/blast-radius"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/blast-radius.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.00968 |
| Opus 5 | $0.00030 | $0.00484 |
| Sonnet 5 | $0.00012 | $0.00194 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
blast-radius scanned grade A with 0 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 10d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to blast-radius — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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, and that is the trap you are walking into. So don't hand back the writeup. Find the one or two facts the whole thing depends on and prove them by running code. Words are where you start, not what you ship.
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.
- You said so. Worthless on its own.
- You pointed at the line. A real
file:line, or the library's own source. - You showed the bad case can't happen. You walked the failure step by step and it doesn't reach.
- You ran it. A script or test that calls the real code and fails loud if you're wrong.
- You reproduced it in the running app.
Any safety fact you can't get to step 4, say so out loud. 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
- 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
whystep 2 to pull the PR and commits. - Find the one fact it's safe because of. Most changes that look scary 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 of the scary cases die at once. Spend your time here, not on a long list of maybes.
- 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.
- 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 realfile:line, a search that finds nothing is still an answer, and never make up a caller or an API. - 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 round up.
- 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 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.
- 10d ago First seen · 51 lines · 61 tokens per session scan A b060df3ca858
blast-radius is a skill published in the GitHub repository J-StaR-Films-Studios/VibeCode-Protocol-Suite (24 stars, last pushed 5d ago), licensed ISC. It adds 61 tokens to every session and 968 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to blast-radius, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
code-review
Reviews code for bugs, security issues, and best practices.
error-translator
A Chinese-language assistant that translates English programming errors and explains what they mean. It covers common errors from languages and frameworks including Python, JavaScript, TypeScript, Java, and others.
eslint-fix
A project-aware assistant for finding and fixing ESLint errors, warnings, and configuration compatibility problems. ESLint is a tool that checks JavaScript and TypeScript code for style and common mistakes.
perf-profiler
A performance investigation guide that uses repeatable measurements and profiling evidence to find where software spends time or resources. Profiling records runtime activity such as CPU use, memory use, database work, or network delays.
log-analyzer
A log-analysis helper that reads application and system logs to find unusual patterns and likely causes. Logs are records of events such as errors, requests, warnings, and service activity.
bug-reproducer
Find likely software bugs in a codebase, rank concrete bug candidates, and prove or reject them with focused regression tests before proposing a fix. Also turn bug reports, stack traces, screenshots, failing behavior, support tickets, and regressions into minimal reproducible cases with red-to-green evidence. Use when…