Blast Radius

# Blast Radius Analysis

Analyze the impact of current code changes using the
code knowledge graph.

## 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(im