Output Formats

Hotspots supports three output formats: JSON (machine-readable), HTML (interactive reports), and Text (human-readable terminal output).

Format Overview

Format	Use Case	Features
JSON	CI/CD, tooling, AI agents	Structured, versioned schema, machine-parseable
HTML	Reports, dashboards, sharing	Interactive, charts, filterable, standalone
Text	Terminal, quick inspection	Color-coded, compact, human-friendly

JSON Format

Machine-readable structured output for programmatic consumption.

Basic Usage

bash

# Snapshot mode JSON
hotspots analyze src/ --format json

# Delta mode JSON
hotspots analyze src/ --mode delta --format json

# With policy evaluation
hotspots analyze src/ --mode delta --policy --format json

Output Structure

json

{
  "schema_version": 2,
  "commit": {
    "sha": "abc123def456...",
    "parents": ["def456..."],
    "timestamp": 1704067200,
    "branch": "main"
  },
  "analysis": {
    "scope": "full",
    "tool_version": "1.0.0"
  },
  "functions": [
    {
      "function_id": "/path/to/file.ts::functionName",
      "file": "/absolute/path/to/file.ts",
      "line": 42,
      "metrics": {
        "cc": 8,
        "nd": 2,
        "fo": 4,
        "ns": 2
      },
      "lrs": 7.2,
      "band": "high"
    }
  ],
  "aggregates": {
    "total_functions": 150,
    "by_band": {
      "low": 80,
      "moderate": 45,
      "high": 20,
      "critical": 5
    },
    "average_lrs": 4.3
  },
  "policy_results": {
    "failed": [],
    "warnings": [
      {
        "id": "watch-threshold",
        "level": "info",
        "function_id": "/path/to/file.ts::someFunction",
        "message": "Function approaching moderate threshold",
        "metadata": {
          "current_lrs": 2.8,
          "threshold": 3.0
        }
      }
    ]
  }
}

Schema Documentation

Complete JSON schema definitions available:

hotspots-output.schema.json - Full output structure
function-report.schema.json - Function analysis format
metrics.schema.json - Raw metrics (CC, ND, FO, NS)
policy-result.schema.json - Policy violations/warnings

See the JSON Schema Reference section below for complete documentation.

Fields Reference

Top-Level Fields

Field	Type	Description
`schema_version`	number	Schema version (currently `2` for snapshot/delta output)
`commit`	object	Git commit metadata
`analysis`	object	Analysis metadata
`functions`	array	Function analysis results
`aggregates`	object	Optional aggregated statistics
`policy_results`	object	Optional policy evaluation results

Commit Metadata

Field	Type	Description
`sha`	string	Git commit SHA (40 chars)
`parents`	string[]	Parent commit SHAs
`timestamp`	number	Unix timestamp
`branch`	string	Branch name (optional)

Function Report

Field	Type	Description
`function_id`	string	Unique identifier: `file::functionName`
`file`	string	Absolute file path
`line`	number	Line number where function starts
`metrics`	object	Raw complexity metrics
`lrs`	number	Leverage Risk Score
`band`	string	Risk band: `low`, `moderate`, `high`, `critical`
`suppression_reason`	string	Optional suppression comment

Metrics Object

Field	Type	Description
`cc`	number	Cyclomatic Complexity
`nd`	number	Nesting Depth
`fo`	number	Fan-Out (function calls)
`ns`	number	Non-Structured exits

TypeScript Integration

bash

npm install @hotspots/types

typescript

import type { HotspotsOutput, FunctionReport } from '@hotspots/types';
import { filterByRiskBand, getHighestRiskFunctions } from '@hotspots/types';

// Parse output
const output: HotspotsOutput = JSON.parse(jsonOutput);

// Filter high-risk functions
const highRisk = filterByRiskBand(output.functions, 'high');

// Get top 10 most complex
const top10 = getHighestRiskFunctions(output.functions, 10);

// Type-safe access
output.functions.forEach((fn: FunctionReport) => {
  console.log(`${fn.function_id}: LRS ${fn.lrs} (${fn.band})`);
});

Python Integration

python

import json

# Parse output
with open('hotspots-output.json') as f:
    output = json.load(f)

# Filter critical functions
critical = [
    fn for fn in output['functions']
    if fn['band'] == 'critical'
]

# Calculate stats
total_functions = len(output['functions'])
avg_lrs = sum(fn['lrs'] for fn in output['functions']) / total_functions

print(f"Total functions: {total_functions}")
print(f"Average LRS: {avg_lrs:.2f}")
print(f"Critical functions: {len(critical)}")

jq Examples

bash

# Extract high-risk functions
jq '.functions[] | select(.band == "high" or .band == "critical")' output.json

# Count by risk band
jq '.aggregates.by_band' output.json

# Top 10 by LRS
jq '.functions | sort_by(.lrs) | reverse | .[0:10]' output.json

# Average LRS
jq '[.functions[].lrs] | add / length' output.json

# Functions with policy violations
jq '.policy_results.failed[] | .function_id' output.json

HTML Format

Interactive HTML reports with charts and visualizations.

Basic Usage

bash

# Snapshot mode HTML
hotspots analyze src/ --mode snapshot --format html

# Delta mode HTML
hotspots analyze src/ --mode delta --format html

# Custom output path
hotspots analyze src/ --mode snapshot --format html --output reports/complexity.html

Default output: .hotspots/report.html

Report Features

Overview Dashboard:

Total functions analyzed
Risk band distribution (pie chart)
Average LRS
Policy violations summary

Function Table:

Sortable by LRS, CC, ND, FO, NS
Filterable by risk band and driver label
Searchable by function name
Color-coded risk levels and driver badges
Action column: per-function refactoring recommendation (driver × quadrant)

Charts (snapshot mode):

Risk band distribution (donut chart)
Historical trend charts: stacked band count, activity risk line, top-1% share line (requires ≥2 prior snapshots; up to 30 history points; hover for per-bar detail)

Delta Mode Additions:

Before/after comparison
Complexity changes (Δ LRS)
New functions highlighted
Removed functions shown
Policy violation details

Opening Reports

bash

# Generate and open in browser
hotspots analyze src/ --mode snapshot --format html
open .hotspots/report.html  # macOS
xdg-open .hotspots/report.html  # Linux
start .hotspots/report.html  # Windows

CI/CD Artifacts

GitHub Actions:

yaml

- uses: Stephen-Collins-tech/hotspots-action@v1
  id: hotspots
  with:
    github-token: ${{ secrets.GITHUB_TOKEN }}

- uses: actions/upload-artifact@v4
  if: always()
  with:
    name: hotspots-report
    path: ${{ steps.hotspots.outputs.report-path }}
    retention-days: 30

GitLab CI:

yaml

artifacts:
  paths:
    - .hotspots/report.html
  expire_in: 1 week

HTML reports are self-contained (embedded CSS/JS):

bash

# Email report
echo "See attached complexity report" | mail -a .hotspots/report.html team@example.com

# Upload to S3
aws s3 cp .hotspots/report.html s3://my-bucket/reports/complexity-$(date +%Y%m%d).html

# Serve with HTTP server
python3 -m http.server 8000 --directory .hotspots
# Open http://localhost:8000/report.html

Text Format

Human-readable terminal output with color coding.

Basic Usage

bash

# Default text output
hotspots analyze src/

# Explicit text format
hotspots analyze src/ --format text

# Delta mode with policy
hotspots analyze src/ --mode delta --policy --format text

Snapshot Mode Output

Hotspots Analysis
================================================================================

Functions by Risk Band:

Critical (LRS ≥ 9.0):
processComplexOrder             /src/orders.ts:142        LRS 10.2  CC 15  ND 4  FO 8  NS 3
handlePaymentFlow               /src/payments.ts:89       LRS 9.5   CC 12  ND 3  FO 6  NS 4

High (6.0 ≤ LRS < 9.0):
validateUserInput               /src/validation.ts:23     LRS 7.8   CC 10  ND 2  FO 5  NS 2
generateReport                  /src/reports.ts:156       LRS 6.5   CC 8   ND 3  FO 4  NS 1

Moderate (3.0 ≤ LRS < 6.0):
formatDate                      /src/utils.ts:45          LRS 4.2   CC 5   ND 1  FO 2  NS 1

Summary:
  Total functions: 150
  Critical: 2
  High: 2
  Moderate: 45
  Low: 101
  Average LRS: 3.2

Snapshot Mode with `--explain`

The --explain flag adds per-function detail: driver label, recommended action, and — for composite-labeled functions — the top near-miss dimensions with their percentile ranks.

hotspots analyze src/ --mode snapshot --format text --explain

processComplexOrder             /src/orders.ts:142
   LRS: 10.2 | Band: critical | Driver: cc
   CC: 15, ND: 4, FO: 8, NS: 3
   Action: Reduce branching; extract sub-functions

handlePaymentFlow               /src/payments.ts:89
   LRS: 9.5 | Band: critical | Driver: composite
   CC: 12, ND: 3, FO: 6, NS: 4
   Action: Multiple complexity dimensions — address the highest first
   Near-threshold: fan_out (P78), cc (P72), nd (P61)

validateUserInput               /src/validation.ts:23
   LRS: 7.8 | Band: high | Driver: nd
   CC: 10, ND: 2, FO: 5, NS: 2
   Action: Reduce nesting depth; early returns help

Near-threshold appears only for composite functions and lists up to 3 dimensions at or above the 40th percentile (i.e., above median across all analysed functions), sorted by percentile rank descending. This makes multi-factor functions interpretable without changing how the driver label is computed.

Delta Mode Output

Delta Analysis
================================================================================

Changed Functions:

processOrder                    /src/orders.ts:42
  Before: LRS 6.5 (high)         CC 8   ND 2  FO 4  NS 1
  After:  LRS 7.2 (high)         CC 10  ND 2  FO 5  NS 2
  Change: +0.7 LRS (+10.8%)      ⚠️  Regression

validateInput                   /src/validation.ts:15
  Before: LRS 5.2 (moderate)     CC 6   ND 2  FO 3  NS 1
  After:  LRS 4.8 (moderate)     CC 5   ND 2  FO 3  NS 1
  Change: -0.4 LRS (-7.7%)       ✅ Improvement

New Functions:
handleNewFeature                /src/features.ts:89       LRS 3.2 (moderate)

Removed Functions:
deprecatedFunction              /src/legacy.ts:123        LRS 8.5 (high)

Summary:
  Changed: 2
  New: 1
  Removed: 1
  Net ΔLRS: +0.3

Delta Mode with Policy Output

Policy Evaluation Results
================================================================================

Policy failures:
- no-regressions: /src/orders.ts::processOrder

Violating functions:
Function                                 Before       After        ΔLRS       Policy
----------------------------------------------------------------------------------------------
processOrder                             high         high         +0.70      no-regressions

Watch Level (approaching moderate threshold):
Function                                 Current LRS  Band
----------------------------------------------------------------
formatCurrency                           2.8          low

Attention Level (approaching high threshold):
Function                                 Current LRS  Band
----------------------------------------------------------------
validateEmail                            5.7          moderate

Summary:
  Blocking failures: 1
  Watch warnings: 1
  Attention warnings: 1

Color Coding

Terminal output uses ANSI colors:

Critical (red): LRS ≥ 9.0
High (yellow): 6.0 ≤ LRS < 9.0
Moderate (blue): 3.0 ≤ LRS < 6.0
Low (green): LRS < 3.0

Disable colors:

bash

NO_COLOR=1 hotspots analyze src/ --format text

Format Comparison

When to Use Each Format

JSON:

✅ CI/CD pipelines
✅ Tooling integration
✅ AI agent consumption
✅ Data analysis
✅ Long-term storage
❌ Human inspection (use HTML/Text)

HTML:

✅ Sharing reports
✅ Dashboards
✅ Historical tracking
✅ Presentations
✅ Non-technical stakeholders
❌ Programmatic parsing (use JSON)

Text:

✅ Terminal inspection
✅ Quick checks
✅ Git hooks
✅ Local development
❌ Automation (use JSON)
❌ Visual analysis (use HTML)

Output Redirection

Save to File

bash

# JSON
hotspots analyze src/ --format json > analysis.json

# Text
hotspots analyze src/ --format text > analysis.txt

# HTML (use --output instead)
hotspots analyze src/ --mode snapshot --format html --output report.html

Pipe to Tools

bash

# Parse with jq
hotspots analyze src/ --format json | jq '.functions[] | select(.band == "critical")'

# Filter with grep
hotspots analyze src/ --format text | grep "Critical"

# Count lines
hotspots analyze src/ --format text | wc -l

CLI Reference - Command-line options
CI/CD & GitHub Action - Using output in pipelines
Configuration - Filter and threshold options

JSON Schema Reference

Hotspots produces versioned JSON output. The schema_version field indicates the format.

Schema Versions

Version	Scope	Added fields
v2 (current)	Snapshot and delta output	`driver`, `driver_detail`, enriched `aggregates` (file_risk, co_change, modules)
v3	Agent-optimized (`--all-functions`)	`fire`/`debt`/`watch`/`ok` quadrant buckets, per-function `action` text
v1	Delta output (legacy constant)	—

Always check schema_version before consuming output in tooling.

Driver Labels

Each function includes an optional driver string identifying the primary source of risk:

Label	Condition	Recommended action
`cyclic_dep`	Function is in a dependency cycle (SCC size > 1)	Break the cycle before adding more callers
`high_complexity`	CC above the Pth percentile	Schedule a refactor; extract sub-functions
`high_churn_low_cc`	touch_count above Pth percentile and CC below (100-P)th	Add regression tests before next change
`high_fanout_churning`	fan_out above Pth percentile and touch above 50th	Extract an interface boundary
`deep_nesting`	ND above the Pth percentile	Flatten with early returns or guard clauses
`high_fanin_complex`	fan_in above Pth percentile and CC above 50th	Extract and stabilize; wide blast radius
`composite`	None of the above specific drivers	Monitor complexity trends

Thresholds are percentile-relative (default P=75, configurable via driver_threshold_percentile). cyclic_dep is the sole absolute check.

`driver_detail` — Near-miss context for composite functions

When a function receives the composite label, driver_detail lists the top dimensions (up to 3) that came closest to firing a specific label, with their percentile rank. Example: "cc (P72), nd (P68)" means CC is at the 72nd percentile and ND at the 68th — notable but below the P75 threshold. Only dimensions above the 40th percentile are included.

driver_detail is omitted from JSON when null (forward-compatible).

Aggregates (Snapshot Mode)

Snapshot output includes an aggregates object with three arrays:

`aggregates.file_risk` — File-Level Risk

Each entry covers one source file, ranked by file_risk_score descending.

typescript

{
  file: "src/api.ts",
  function_count: 12,
  loc: 340,
  max_cc: 14,
  avg_cc: 6.8,
  critical_count: 2,
  file_churn: 180,
  file_risk_score: 8.3   // max_cc×0.4 + avg_cc×0.3 + log2(fn_count+1)×0.2 + churn×0.1
}

`aggregates.co_change` — Co-Change Coupling

Pairs of files that frequently change together in the same commit. High coupling with no static dependency = hidden implicit coupling.

typescript

{
  file_a: "hotspots-cli/src/main.rs",
  file_b: "hotspots-core/src/aggregates.rs",
  co_change_count: 14,
  coupling_ratio: 0.78,
  has_static_dep: false,
  risk: "high"   // "high" | "moderate" | "expected" | "low"
}

risk: "expected" means a static import exists between the files — the co-change is explained. Default window: 90 days; minimum count: 3.

`aggregates.modules` — Module Instability

Robert Martin's instability metric at the directory level: instability = efferent / (afferent + efferent).

typescript

{
  module: "hotspots-core/src",
  file_count: 12,
  function_count: 409,
  avg_complexity: 3.2,
  afferent: 8,       // external modules depending on this one
  efferent: 3,       // external modules this one depends on
  instability: 0.27, // near 0 = risky to change; near 1 = safe
  module_risk: "high"
}

Schema Files

JSON Schema definitions are available in the schemas/ directory:

hotspots-output.schema.json — Complete output schema
function-report.schema.json — Individual function analysis
metrics.schema.json — Raw metrics (CC, ND, FO, NS)
policy-result.schema.json — Policy violation/warning format

All schemas follow JSON Schema Draft 07.

Examples

Extract Critical Functions (JSON)

bash

hotspots analyze src/ --format json | \
  jq -r '.functions[] | select(.band == "critical") | "\(.function_id): \(.lrs)"'

Generate Report Card (Text)

bash

hotspots analyze src/ --format text | \
  grep -A 10 "Summary:"

Track Complexity Over Time (JSON)

bash

# Daily snapshots
hotspots analyze src/ --mode snapshot --format json > "reports/$(date +%Y%m%d).json"

# Compare last 7 days
for file in reports/*.json; do
  avg_lrs=$(jq '.aggregates.average_lrs' "$file")
  echo "$(basename $file .json): $avg_lrs"
done

Custom HTML Dashboard

Embed HTML report in iframe:

html

<!DOCTYPE html>
<html>
<head>
  <title>Complexity Dashboard</title>
</head>
<body>
  <h1>Latest Complexity Report</h1>
  <iframe src=".hotspots/report.html" width="100%" height="800px"></iframe>
</body>
</html>

Need more examples? Check out examples/output-formats/.

Using in CI/CD? See CI/CD & GitHub Action for pipeline integration examples.

Output Formats ​

Format Overview ​

JSON Format ​

Basic Usage ​

Output Structure ​

Schema Documentation ​

Fields Reference ​

Top-Level Fields ​

Commit Metadata ​

Function Report ​

Metrics Object ​

TypeScript Integration ​

Python Integration ​

jq Examples ​

HTML Format ​

Basic Usage ​

Report Features ​

Opening Reports ​

CI/CD Artifacts ​

Sharing Reports ​

Text Format ​

Basic Usage ​

Snapshot Mode Output ​

Snapshot Mode with --explain ​

Delta Mode Output ​

Delta Mode with Policy Output ​

Color Coding ​

Format Comparison ​

When to Use Each Format ​

Output Redirection ​

Save to File ​

Pipe to Tools ​

Related Documentation ​

JSON Schema Reference ​

Schema Versions ​

Driver Labels ​

driver_detail — Near-miss context for composite functions ​

Aggregates (Snapshot Mode) ​

aggregates.file_risk — File-Level Risk ​

aggregates.co_change — Co-Change Coupling ​

aggregates.modules — Module Instability ​

Schema Files ​

Examples ​

Extract Critical Functions (JSON) ​

Generate Report Card (Text) ​

Track Complexity Over Time (JSON) ​

Custom HTML Dashboard ​

Output Formats

Format Overview

JSON Format

Basic Usage

Output Structure

Schema Documentation

Fields Reference

Top-Level Fields

Commit Metadata

Function Report

Metrics Object

TypeScript Integration

Python Integration

jq Examples

HTML Format

Basic Usage

Report Features

Opening Reports

CI/CD Artifacts

Sharing Reports

Text Format

Basic Usage

Snapshot Mode Output

Snapshot Mode with `--explain`

Delta Mode Output

Delta Mode with Policy Output

Color Coding

Format Comparison

When to Use Each Format

Output Redirection

Save to File

Pipe to Tools

Related Documentation

JSON Schema Reference

Schema Versions

Driver Labels

`driver_detail` — Near-miss context for composite functions

Aggregates (Snapshot Mode)

`aggregates.file_risk` — File-Level Risk

`aggregates.co_change` — Co-Change Coupling

`aggregates.modules` — Module Instability

Schema Files

Examples

Extract Critical Functions (JSON)

Generate Report Card (Text)

Track Complexity Over Time (JSON)

Custom HTML Dashboard