
claude-insights parses your Claude Code /insight HTML report and generates personalized CLAUDE.md rules, custom skills, hook configs, and a prioritized to-do list — all derived from your actual friction patterns.
Claude Code's /insights command is one of its most underrated features. It analyzes your last 30 days of usage and generates a detailed HTML report: friction patterns, strengths, CLAUDE.md suggestions, workflow recommendations, and more.
The problem? The report is read-only. It's a beautiful HTML page that you read, nod at, and then close. The friction patterns it identifies are real — but translating them into CLAUDE.md rules, custom skills, and settings changes is manual, tedious work that most developers skip entirely.
That's the gap claude-insights fills.
claude-insights is an open-source CLI tool that parses your /insight report HTML and generates production-ready output files — personalized to your specific friction patterns, not generic templates.
One command:
npx claude-insights analyze ~/.claude/usage-data/report.html
Generates:
| Output File | What It Contains |
|---|---|
insights-todo.md | Prioritized task table with steps, time estimates, and expected friction reduction |
CLAUDE.md-additions.md | Ready-to-paste rules organized by section (General, CSS, Testing, Debugging) |
.claude/settings-insights.json | Hook configurations extracted from your report |
.claude/skills/*.SKILL.md | Custom skill files — one per friction pattern — with triggers, steps, rules, and verification checklists |
insights-README.md | Placement guide explaining where each file goes |
The tool follows a three-stage pipeline:
Uses cheerio to extract structured data from the HTML report — stats, project areas, friction categories with examples, CLAUDE.md suggestions with rationale, feature recommendations, workflow patterns, and more.
Parsing report...
Parsed report: 982 messages, Jan 5 — Feb 3, 2026
3 friction areas, 4 strengths, 5 CLAUDE.md suggestions
This is where the tool does its heavy lifting. For each friction pattern in your report, it:
Writes all output files to your chosen directory, creating the .claude/skills/ structure automatically.
This is the part that matters most. Each friction pattern becomes a structured skill file that Claude Code can invoke with a slash command.
Here's a real example — generated from a report where Claude kept proposing fixes without checking the codebase first:
---
name: solutions-codebase-verification
description: |
Use when encountering premature solutions without codebase verification,
especially when adding new API endpoints to an existing controller,
or refactoring shared utility modules.
---
## When to Use This Skill
- When a task involves premature solutions without codebase verification.
- When adding new API endpoints to an existing controller.
- When refactoring shared utility modules.
## Steps
1. **Diagnose**: Read the relevant files and map the existing patterns.
Identify boundaries, ownership, and current behavior before changing
anything.
2. **Identify constraints**: List what must NOT change, which components
are affected, and document your assumptions. Get confirmation.
3. **Propose approach**: Describe your planned fix and explain why it
avoids the known failure patterns listed in "What Goes Wrong" below.
Wait for approval.
4. **Implement**: Apply the most minimal, narrowly-scoped change possible.
5. **Verify**: Confirm the fix works AND doesn't regress related components.
## Rules
- Before proposing a fix, always verify the approach against the existing
codebase patterns first
- Do NOT suggest options or solutions without confirming they work in this
specific codebase
- After implementing, verify the fix doesn't regress related components
## What Goes Wrong
Review these failure patterns before implementing. Your fix must not
repeat them:
- When adding a new endpoint, Claude reused a pattern from a different
controller that didn't match the authentication middleware in this one,
requiring a full rewrite after review.
- When refactoring the shared utility, Claude moved functions without
checking downstream consumers, breaking two dependent services.
## Verification Checklist
- [ ] Fix addresses the specific issue the user reported
- [ ] Change follows existing codebase patterns found during diagnosis
- [ ] Change is narrowly scoped — minimal blast radius
- [ ] Related/sibling components verified — no regressions
- [ ] Approach was proposed and confirmed before implementation
After placing this file in .claude/skills/, you invoke it with /solutions-codebase-verification at the start of any relevant task. Claude reads the skill, follows the steps, checks against your documented failure patterns, and runs through the verification checklist before claiming the work is done.
The key insight: these skills aren't generic. They contain your friction examples, your failure patterns, and your codebase-specific rules. That's what makes them effective.
The tool doesn't just dump rules — it categorizes them by domain and includes the rationale from your report:
## General Rules
Before proposing a fix, always verify the approach against the existing
codebase patterns first. Do NOT suggest options or solutions without
confirming they work in this specific codebase.
> _Why: In multiple sessions Claude suggested approaches without verifying
> them against the codebase, leading to wrong patterns (e.g., incorrect
> test setup, mismatched import conventions), requiring repeated user
> corrections._
## CSS & Styling
When working with CSS in component libraries (especially scoped styles
and design tokens): 1) Always scope CSS fixes narrowly to avoid breaking
other components, 2) Test that changes don't regress sibling views.
## Testing
Follow the existing test patterns in the file's directory — check sibling
test files before writing new ones. Match existing mock/setup patterns
for unit tests and page object patterns for E2E tests.
## Debugging
When debugging production or intermittent issues, do NOT jump to
conclusions. First: reproduce locally. Second: add targeted diagnostic
logging. Third: only propose a fix when the root cause is confirmed.
You copy the rules you want into your project's CLAUDE.md. The _Why annotations help you decide which rules matter most for your workflow.
Instead of reading a report and trying to figure out what to do first, you get a ranked action plan:
| # | Task | Priority | Est Time |
|---|---|---|---|
| 1 | Address friction: "Premature Solutions Without Codebase Verification" | High | 5 min |
| 2 | Address friction: "Repeated Styling and Layout Failures" | High | 5 min |
| 3 | Address friction: "Debugging Wrong Root Causes" | High | 5 min |
| 4 | Add CLAUDE.md rule: "Before proposing a fix, always verify..." | High | 2 min |
| 5 | Set up Hooks | Medium | 10 min |
| 6 | Try workflow: High friction from premature solutions | Medium | 5 min |
Each task includes concrete steps: which file to copy, where to paste it, and how to test it.
The tool is built with:
The codebase is ~500 lines of source across 5 files. No frameworks, no runtime dependencies beyond cheerio and commander.
There are several Claude Code usage tools in the ecosystem, but they solve different problems:
| Tool | Focus |
|---|---|
| ccusage | Token/cost analysis from JSONL session files |
| claude-code-usage-analyzer | Cost breakdown by model and token type |
| awesome-claude-skills | Curated collections of hand-written skills |
| claude-code-skill-factory | Toolkit for manually building skills |
| claude-insights | Automatically generates personalized skills, rules, and settings from your /insight report |
The distinction: existing tools either analyze costs or provide generic pre-built skills. claude-insights bridges the gap between Anthropic's insight analysis and your project configuration — automatically.
npm install -g claude-insights
npx claude-insights analyze ~/.claude/usage-data/report.html
npx claude-insights analyze ~/.claude/usage-data/report.html -o ./my-project
CLAUDE.md.claude/settings.json.claude/skills//skill-name on your next taskclaude-insights is open source and MIT licensed. Contributions, issues, and feedback are welcome on GitHub.
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