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…
Skill by dotts-h
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/dotts-h-blast-radius
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/blast-radius
What's inside
- Skill name
blast-radius- Description
- 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.
- License
- MIT
- Instructions
- 46 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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. 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. 6. For a big or wide change, run parallel verification subagents across models. Give each subagent the same question, then 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.** 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.
From dotts-h/qstack, MIT.
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Reproduce reported defects through the target app's real UI or CLI on at least two recorded runs, verify existing fixes against baseline and patched builds…
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setup-qstack
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Configure which models the qstack how and why skills give their subagents and at what reasoning budget.
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Pin a reproduced bug or regression signal with a focused executable check that fails before the fix and passes after it, or select the closest live…
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Apply to any non-trivial work, including edits, migrations, analyses, and checks.
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principle-sequence-verifiable-units
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Apply to multi-step work such as sweeps, migrations, and runs of similar edits, and to how you stack commits and PRs.
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in-your-own-words
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Restate the testing goal, target surface, and risk hypothesis in your own words before test execution.
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principle-explain-the-number
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Apply before you trust, report, or act on a number you measured.
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principle-never-block-on-the-human
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Apply when tempted to ask 'should I do X?' on reversible work.
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how
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Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which…
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maintain-verification-skill
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Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature…
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 19, 2026 (10 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/dotts-h/qstack
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from dotts-h
- 0.567score
qstack-mode
dotts-h
Run structured QA workflows in Cursor: test chartering, real-surface reproduction with recorded runs, defect triage, baseline-versus-patch fix verification…
SkillAFreshness: AClaude Code +9 - 0.567score
triage-defect
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Triage bug reports with bounded cause tracing, duplicate detection, bug-versus-feature classification, and self-contained defect report formatting.
SkillAFreshness: AClaude Code +9 - 0.567score
reproduce-issue
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Reproduce reported defects through the target app's real UI or CLI on at least two recorded runs, verify existing fixes against baseline and patched builds…
SkillAFreshness: AClaude Code +9 - 0.565score
setup-qstack
dotts-h
Configure which models the qstack how and why skills give their subagents and at what reasoning budget.
SkillAFreshness: AClaude Code +9 - 0.561score
regression-pin
dotts-h
Pin a reproduced bug or regression signal with a focused executable check that fails before the fix and passes after it, or select the closest live…
SkillAFreshness: AClaude Code +9 - 0.561score
principle-build-the-lever
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Apply to any non-trivial work, including edits, migrations, analyses, and checks.
SkillAFreshness: AClaude Code +9
Cite this page
blast-radius skill. Agent Mart. https://agentmart.dev/skills/dotts-h-blast-radius (last updated 2026-10-24)