blast-radius
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.
Works with
---
name: blast-radius
description: 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.
license: MIT
---
# 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:
```bash
GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)
```
**If gauntlet is not installed** (GRAPH_QUERY is empty):
Fall back to a manual impact analysis using `git diff`
and `grep` to trace imports and call sites. Skip graph
steps and go directly to step 3 (manual mode).
**If gauntlet is installed but no graph.db exists**:
Tell the user: "Run `/gauntlet-graph build` first."
## Steps
1. **Show current changes**: Run `git diff --stat` to
show the user what files changed.
2. **Run impact analysis** (requires gauntlet):
```bash
python3 "$GRAPH_QUERY" \
--action impact --base-ref HEAD --depth 2
```
**Fallback tier 1 (sem available, no gauntlet)**:
Use sem for cross-file dependency tracing:
```bash
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):
```bash
# 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.
3. **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.
4. **Highlight untested functions**: List any affected
functions that lack test coverage (no TESTED_BY edge).
5. **Show overall risk**: Display the overall risk level
(low/medium/high) based on the maximum risk score.
6. **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:
```bash
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 |More AI & ML skills
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