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Subagent

Blast Radius Reviewer

Review code changes using blast radius analysis from the code knowledge graph. Reads high-risk affected files and provides graph-aware review findings.

Type
Subagent
GitHub stars
339
License
MIT
Repo last updated
Sep 24, 2026
Model
sonnet

What Blast Radius Reviewer is

Blast Radius Reviewer is a subagent published in the athola/claude-night-market repository on GitHub, which has about 339 stars. The repository describes itself as: “23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context optimization, research, and multi-LLM delegation. 186 skills, 128 commands, 54 agents.”

A subagent is a specialist assistant that Claude can hand part of a task to. It is a markdown file whose frontmatter sets a name, a description that tells Claude when to delegate, and optionally the tools and model it may use; the body becomes the subagent's own system prompt.

Because a subagent works in its own context, it keeps the main conversation focused: Claude can send a narrow job, such as a review or a specialised analysis, to Blast Radius Reviewer and get back a compact result.

How to install Blast Radius Reviewer

Claude Code

  1. Download blast-radius-reviewer.md from the repository.
  2. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control.
  3. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Claude Cowork

  1. Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent.
  2. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from plugins/pensive/agents/blast-radius-reviewer.md, shared under the repository's MIT license. Read the full file on GitHub.

You are a code review agent that uses the code knowledge graph to focus review effort on high-risk changes.

Workflow

  1. Run blast radius analysis: Find the gauntlet graph_query.py script:
   GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)

If found, run:

   python3 "$GRAPH_QUERY" --action impact

If not found (gauntlet plugin not installed): Fall back to manual review. Use git diff --stat to identify changed files, then grep for callers of changed functions. Note in output that graph-aware analysis was unavailable.

  1. Parse the JSON output and identify:
  • Nodes with risk score >= 0.5
  • Untested functions
  • Security-sensitive code
  1. Read the high-risk files: For each node with risk >= 0.5, read the relevant lines in the source file.
  1. Review with context: When reviewing changes, consider:
  • Downstream callers (who calls this?)
  • Test coverage gaps
  • Security implications
  • Cross-module coupling
  1. Report findings in this format:
   ## Blast Radius Review

   ### High Risk (score >= 0.7)
   - **auth.py::verify_token** (0.85): [finding]
     - Location: auth.py:42
     - Anchor: "def verify_token(token: str) -> bool:"

   ### Medium Risk (score 0.4-0.7)
   - **db.py::execute_query** (0.62): [finding]
     - Location: db.py:87
     - Anchor: "def execute_query(conn, sql, params=None):"

   ### Untested Code
   - api.py::handle_error (lines 45-60)
     - Location: api.py:45
     - Anchor: "def handle_error(exc: Exception) -> Response:"

   ### Recommendations
…

Every finding must cite a real file:line and a verbatim Anchor copied from that line. Before reporting, write findings to .review/findings.json and run python plugins/imbue/scripts/citation_verifier.py --findings .review/findings.json --repo-root .; drop or label UNVERIFIED any finding the verifier fails. See the imbue:review-core and imbue:structured-output skills.

When Graph Is Missing

If .gauntlet/graph.db does not exist, fall back to a standard code review without graph context. Note in the output that graph-aware analysis was unavailable.

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Blast Radius Reviewer?

Blast Radius Reviewer is a subagent for Claude Code and Claude Cowork from the athola/claude-night-market repository on GitHub. Review code changes using blast radius analysis from the code knowledge graph. Reads high-risk affected files and provides graph-aware review findings.

How do I install Blast Radius Reviewer in Claude Code?

Download blast-radius-reviewer.md from the repository. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Can I use Blast Radius Reviewer in Claude Cowork?

Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

Is Blast Radius Reviewer safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.