Night Market Skill — ported from claude-night-market/pensive. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

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:

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):

   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
       rg -l "$(basename $f .py)" --type py . 2>/dev/null
     done | sort -u
   else
     git diff --name-only HEAD | while read f; do
       grep -rl "$(basename $f .py)" --include="*.py" . 2>/dev/null
     done | sort -u
   fi

3. Display results in priority order:

   Format the output as a table:

   Risk  | Node                    | File          | Reason
   0.85  | auth.py::verify_token   | auth.py:45    | untested, security
   0.62  | db.py::execute_query    | db.py:112     | high fan-in
   0.41  | api.py::handle_request  | api.py:78     | flow participant

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"

Risk Scoring Model

Five weighted factors (sum capped at 1.0):