ai-data-report — community ai-data-report, hipoteca-findr-dify, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0

About this Skill

Perfect for Development Agents needing automated project report generation with Next.js Generates data-driven reports about the project. Use for initial project reports or session summaries.

theam theam
[0]
[0]
Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reviewed Landing Page Review Score: 9/11

Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review Locale and body language aligned
Review Score
9/11
Quality Score
51
Canonical Locale
en
Detected Body Locale
en

Perfect for Development Agents needing automated project report generation with Next.js Generates data-driven reports about the project. Use for initial project reports or session summaries.

Core Value

Empowers agents to generate comprehensive data-driven reports in Markdown format, utilizing Git for version control and history tracking, and saves them in a designated .claude/reports/ directory

Ideal Agent Persona

Perfect for Development Agents needing automated project report generation with Next.js

Capabilities Granted for ai-data-report

Automating project report generation
Generating detailed reports for project managers
Committing reports to Git for history tracking

! Prerequisites & Limits

  • Requires Next.js
  • Saves reports in .claude/reports/ directory
  • Commits reports to Git repository

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is ai-data-report?

Perfect for Development Agents needing automated project report generation with Next.js Generates data-driven reports about the project. Use for initial project reports or session summaries.

How do I install ai-data-report?

Run the command: npx killer-skills add theam/hipoteca-findr-dify/ai-data-report. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for ai-data-report?

Key use cases include: Automating project report generation, Generating detailed reports for project managers, Committing reports to Git for history tracking.

Which IDEs are compatible with ai-data-report?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for ai-data-report?

Requires Next.js. Saves reports in .claude/reports/ directory. Commits reports to Git repository.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add theam/hipoteca-findr-dify/ai-data-report. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use ai-data-report immediately in the current project.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

ai-data-report

Install ai-data-report, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Skill: AI Data Report

Description

Generates data-driven reports about the project. Use /ai-data-report to invoke.

Where reports are saved

  • Location: .claude/reports/
  • Naming: YYYY-MM-DD-[type].md (e.g., 2026-01-22-session.md, 2026-01-22-initial.md)
  • Git: Reports are committed to the repo for history tracking

Modes

1. Initial Report (first time on project)

Generates a complete report with:

## 📊 Project Report

**Production URL:** [production URL]
**GitHub URL:** [repo URL]
**Development time:** [estimated hours and context]

### Services used:
| Service | Purpose |
|---------|---------|
| [Service 1] | [What it does] |
| [Service 2] | [What it does] |
...

### Flow when someone uses the app:
1. [Step 1]
2. [Step 2]
...

### Tech stack:
- Backend: [technology]
- Frontend: [technology]
- Database: [technology]
- Hosting: [technology]

### Deployment:
- [How it deploys]
- [Where env variables are stored]

2. Session Report (when finishing work)

Generates a session summary:

## 📝 Session Summary

**Date:** [date]
**Approximate duration:** [time]

### Changes made:
| Area | Change | Files |
|------|--------|-------|
| [area] | [description] | [files] |

### Commits:
- `[hash]` [message]

### Bugs found/fixed:
- [bug 1]

### Suggested next steps:
- [ ] [task 1]
- [ ] [task 2]

### Metrics:
| Metric | Value |
|--------|-------|
| Lines changed | +X / -Y |
| Files modified | N |
| Commits | N |
| **Time - Claude** | ~Xh Xmin (coding, debugging, testing) |
| **Time - Human** | ~Xmin (reviewing, testing, giving feedback) |

Instructions for Claude

When user invokes /project-report:

  1. Detect mode:

    • If first interaction or they ask for "initial report" → Mode 1
    • If they ask for "session summary" or "what did we do" → Mode 2
  2. Gather data:

    • Read package.json, requirements.txt, .env.example to detect services
    • Check git log for recent commits
    • Check git remote -v for URLs
    • Look for production URLs in README or configs
  3. Be data-driven:

    • Use real data from code, don't make things up
    • If data is missing, indicate "[pending configuration]"
    • Include specific numbers when possible
  4. Format:

    • Use tables for structured information
    • Use emojis for main sections
    • Be concise but complete

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