developer-growth-analysis
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
What this skill does
# Developer Growth Analysis
This skill provides personalized feedback on your recent coding work by analyzing your Claude Code chat interactions and identifying patterns that reveal strengths and areas for growth.
## When to Use This Skill
Use this skill when you want to:
- Understand your development patterns and habits from recent work
- Identify specific technical gaps or recurring challenges
- Discover which topics would benefit from deeper study
- Get curated learning resources tailored to your actual work patterns
- Track improvement areas across your recent projects
- Find high-quality articles that directly address the skills you're developing
This skill is ideal for developers who want structured feedback on their growth without waiting for code reviews, and who prefer data-driven insights from their own work history.
## What This Skill Does
This skill performs a six-step analysis of your development work:
1. **Reads Your Chat History**: Accesses your local Claude Code chat history from the past 24-48 hours to understand what you've been working on.
2. **Identifies Development Patterns**: Analyzes the types of problems you're solving, technologies you're using, challenges you encounter, and how you approach different kinds of tasks.
3. **Detects Improvement Areas**: Recognizes patterns that suggest skill gaps, repeated struggles, inefficient approaches, or areas where you might benefit from deeper knowledge.
4. **Generates a Personalized Report**: Creates a comprehensive report showing your work summary, identified improvement areas, and specific recommendations for growth.
5. **Finds Learning Resources**: Uses HackerNews to curate high-quality articles and discussions directly relevant to your improvement areas, providing you with a reading list tailored to your actual development work.
6. **Sends to Your Slack DMs**: Automatically delivers the complete report to your own Slack direct messages so you can reference it anytime, anywhere.
## How to Use
Ask Claude to analyze your recent coding work:
```
Analyze my developer growth from my recent chats
```
Or be more specific about which time period:
```
Analyze my work from today and suggest areas for improvement
```
The skill will generate a formatted report with:
- Overview of your recent work
- Key improvement areas identified
- Specific recommendations for each area
- Curated learning resources from HackerNews
- Action items you can focus on
## Instructions
When a user requests analysis of their developer growth or coding patterns from recent work:
1. **Access Chat History**
Read the chat history from `~/.claude/history.jsonl`. This file is a JSONL format where each line contains:
- `display`: The user's message/request
- `project`: The project being worked on
- `timestamp`: Unix timestamp (in milliseconds)
- `pastedContents`: Any code or content pasted
Filter for entries from the past 24-48 hours based on the current timestamp.
2. **Analyze Work Patterns**
Extract and analyze the following from the filtered chats:
- **Projects and Domains**: What types of projects was the user working on? (e.g., backend, frontend, DevOps, data, etc.)
- **Technologies Used**: What languages, frameworks, and tools appear in the conversations?
- **Problem Types**: What categories of problems are being solved? (e.g., performance optimization, debugging, feature implementation, refactoring, setup/configuration)
- **Challenges Encountered**: What problems did the user struggle with? Look for:
- Repeated questions about similar topics
- Problems that took multiple attempts to solve
- Questions indicating knowledge gaps
- Complex architectural decisions
- **Approach Patterns**: How does the user solve problems? (e.g., methodical, exploratory, experimental)
3. **Identify Improvement Areas**
Based on the analysis, identify 3-5 specific areas where the user could improve. These should be:
- **Specific** (not vague like "improve coding skills")
- **Evidence-based** (grounded in actual chat history)
- **Actionable** (practical improvements that can be made)
- **Prioritized** (most impactful first)
Examples of good improvement areas:
- "Advanced TypeScript patterns (generics, utility types, type guards) - you struggled with type safety in [specific project]"
- "Error handling and validation - I noticed you patched several bugs related to missing null checks"
- "Async/await patterns - your recent work shows some race conditions and timing issues"
- "Database query optimization - you rewrote the same query multiple times"
4. **Generate Report**
Create a comprehensive report with this structure:
```markdown
# Your Developer Growth Report
**Report Period**: [Yesterday / Today / [Custom Date Range]]
**Last Updated**: [Current Date and Time]
## Work Summary
[2-3 paragraphs summarizing what the user worked on, projects touched, technologies used, and overall focus areas]
Example:
"Over the past 24 hours, you focused primarily on backend development with three distinct projects. Your work involved TypeScript, React, and deployment infrastructure. You tackled a mix of feature implementation, debugging, and architectural decisions, with a particular focus on API design and database optimization."
## Improvement Areas (Prioritized)
### 1. [Area Name]
**Why This Matters**: [Explanation of why this skill is important for the user's work]
**What I Observed**: [Specific evidence from chat history showing this gap]
**Recommendation**: [Concrete step(s) to improve in this area]
**Time to Skill Up**: [Brief estimate of effort required]
---
[Repeat for 2-4 additional areas]
## Strengths Observed
[2-3 bullet points highlighting things you're doing well - things to continue doing]
## Action Items
Priority order:
1. [Action item derived from highest priority improvement area]
2. [Action item from next area]
3. [Action item from next area]
## Learning Resources
[Will be populated in next step]
```
5. **Search for Learning Resources**
Use Rube MCP to search HackerNews for articles related to each improvement area:
- For each improvement area, construct a search query targeting high-quality resources
- Search HackerNews using RUBE_SEARCH_TOOLS with queries like:
- "Learn [Technology/Pattern] best practices"
- "[Technology] advanced patterns and techniques"
- "Debugging [specific problem type] in [language]"
- Prioritize posts with high engagement (comments, upvotes)
- For each area, include 2-3 most relevant articles with:
- Article title
- Publication date
- Brief description of why it's relevant
- Link to the article
Add this section to the report:
```markdown
## Curated Learning Resources
### For: [Improvement Area]
1. **[Article Title]** - [Date]
[Description of what it covers and why it's relevant to your improvement area]
[Link]
2. **[Article Title]** - [Date]
[Description]
[Link]
[Repeat for other improvement areas]
```
6. **Present the Complete Report**
Deliver the report in a clean, readable format that the user can:
- Quickly scan for key takeaways
- Use for focused learning planning
- Reference over the next week as they work on improvements
- Share with mentors if they want external feedback
7. **Send Report to Slack DMs**
Use Rube MCP to send the complete report to the user's own Slack DMs:
- Check if Slack connection is active via RUBE_SEARCH_TOOLS
- If not connected, use RUBE_MANAGE_CONNECTIONS to initiate Slack auth
- Use RUBE_MULTI_EXECUTE_TOOL to send the report as a formatted message:
- Send the report title and period as the first message
- Break the report into logical sections (Summary, Improvements, Strengths, Actions, Resources)
- Format each section as aRelated in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".