mcpbeat Sign in

Blast Radius Agent Skill

Analyzes code change impact with risk scoring and affected-node mapping. Use before merging to understand what a change touches and what lacks test coverage.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
324
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/athola/claude-night-market --skill blast-radius

The instruction itself

7 sections, as written by the author

Blast Radius Analysis

Analyze the impact of current code changes using the

code knowledge graph.

When NOT To Use

  • Reading the changed code for defects (use pensive:bug-review)
  • The code graph is missing or stale (use gauntlet:graph-build)

Prerequisites

This skill requires the gauntlet plugin for graph

data. Check if it's available:

GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)

If gauntlet is not installed (GRAPH_QUERY is empty):

Fall back to a manual impact analysis using git diff

and grep to trace imports and call sites. Skip graph

steps and go directly to step 3 (manual mode).

If gauntlet is installed but no graph.db exists:

Tell the user: "Run /gauntlet-graph build first."

Steps

  • Show current changes: Run git diff --stat to

show the user what files changed.

  • Run impact analysis (requires gauntlet):
   python3 "$GRAPH_QUERY" \
       --action impact --base-ref HEAD --depth 2

Fallback tier 1 (sem available, no gauntlet):

Use sem for cross-file dependency tracing:

   if command -v sem &>/dev/null; then
     sem impact --json <changed-file>
   fi

This traces real function-level dependencies instead

of filename matching. See leyline:sem-integration

for detection patterns.

Fallback tier 2 (no sem, no gauntlet): Trace

callers of changed functions with rg (or grep):

   # Prefer rg for speed; fall back to grep
   if command -v rg &>/dev/null; then
     git diff --name-only HEAD | while read f; do
       stem="${f%.*}"; stem="${stem##*/}"
       [ -z "$stem" ] && continue  # skip dotfiles (.gitignore etc.)
       rg -l "$stem" . 2>/dev/null
     done | sort -u
   else
     git diff --name-only HEAD | while read f; do
       stem="${f%.*}"; stem="${stem##*/}"
       [ -z "$stem" ] && continue  # skip dotfiles (.gitignore etc.)
       grep -rl "$stem" . 2>/dev/null
     done | sort -u
   fi

Note: this searches all file types. For Python-only

projects, add --type py to rg or --include="*.py"

to grep to reduce false positives.

  • Display results in priority order:

Format the output as a table:

   Risk  | Node                    | File          | Anchor                          | Reason
   0.85  | auth.py::verify_token   | auth.py:45    | `def verify_token(token):`      | untested, security
   0.62  | db.py::execute_query    | db.py:112     | `cursor.execute(query, params)` | high fan-in
   0.41  | api.py::handle_request  | api.py:78     | `def handle_request(req):`      | flow participant

The Anchor column is the verbatim source text at the cited line.

It lets a reviewer confirm the finding without re-running the tool.

  • Highlight untested functions: List any affected

functions that lack test coverage (no TESTED_BY edge).

  • Show overall risk: Display the overall risk level

(low/medium/high) based on the maximum risk score.

  • Suggest actions:
  • For high-risk nodes: "Consider adding tests before

merging"

  • For security-sensitive nodes: "Review authentication

and authorization logic carefully"

  • For high-fan-in nodes: "Changes here affect many

callers; verify backward compatibility"

Verify Findings Are Grounded (blast-radius:findings-verified)

Every finding must cite a real location and a verbatim anchor. Write

findings to .review/findings.json and confirm each citation resolves:

python plugins/imbue/scripts/citation_verifier.py \
  --findings .review/findings.json --repo-root .

Drop or label UNVERIFIED any finding the verifier fails (exit 1); only

verified findings enter the report. See Skill(imbue:review-core) Step 5

and Skill(imbue:structured-output) for the schema.

Exit Criteria

  • [ ] Results table lists every affected node with a File (file:line)

and verbatim Anchor column.

  • [ ] Overall risk level (low/medium/high) is displayed based on the

maximum risk score.

  • [ ] Every reported finding carries a Location + verbatim Anchor

confirmed by citation_verifier.py (exit 0), or unverified

findings were dropped or labeled UNVERIFIED.

Risk Scoring Model

Five weighted factors (sum capped at 1.0):

| Factor | Weight | Meaning |

|--------|--------|---------|

| Test gap | 0.30 | No test coverage |

| Security | 0.20 | Auth/crypto/SQL keywords |

| Flow participation | 0.25 | Part of execution flows |

| Cross-community | 0.15 | Called from other modules |

| Caller count | 0.10 | High fan-in function |

Other skills for the same job

different authors, same section of the catalogue
Webapp Testing
by anthropics
vendor ×12

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

6k tokens scripts
Finishing A Development Branch
by ZhanlinCui
×7

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

1k tokens
Test Driven Development
by w95
×7

Use when implementing any feature or bugfix, before writing implementation code

2k tokens
Systematic Debugging
by ratacat
×7

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

10k tokens scripts
Verification Before Completion
by ZhanlinCui
×6

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

1k tokens
Backtest Expert
by BaggaT236
×3

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

15k tokens scripts
Adaptyv
by christophacham
×3

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

16k tokens
Aeon
by christophacham
×3

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

19k tokens

How to use it

Copy the folder

Take athola/blast-radius from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.