Agent skill

Report Generator

by haoyu-haoyu in haoyu-haoyu/Multi-AI-Workflow

Multi-AI collaborative report generator. An agent skill from haoyu-haoyu/Multi-AI-Workflow.

MITAuto-check passedDevelopment

Install Report Generator

skills CLI
$ npx skills add haoyu-haoyu/Multi-AI-Workflow --skill report-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install haoyu-haoyu/Multi-AI-Workflow report-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/haoyu-haoyu/Multi-AI-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.maw/skills/report-generator .claude/skills/report-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
report-generator
GitHub stars
109
Token cost
~388 tokens
SKILL.md length
73 words
Files
2
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Multi-AI collaborative report generator. An agent skill from haoyu-haoyu/Multi-AI-Workflow.

  • Development work in your project
  • SKILL.md covers Features, Quick Start, Output and Workflow
  • Runs Python scripts from its folder; calls python

What it does

Report Generator is an agent skill from haoyu-haoyu/Multi-AI-Workflow. Multi-AI collaborative report generator. Uses Claude for planning/writing and Gemini for diagram generation. Creates professional reports with auto-generated figures from your research content.

Its SKILL.md is about 390 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `report_generator.py`).

It sits in Development. It works with Google Gemini and TypeScript. The repository describes itself as: Multi-AI orchestration framework for Claude Code — coordinate Claude, Codex, and Gemini with 7 workflow modes, parallel execution, and session unification. The licence is MIT.

When your agent uses it

  • Development work in your project

Example prompts

  • “/report-generator”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 1df1a99. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Report Generator loads about 388 tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 73 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~388

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from haoyu-haoyu/Multi-AI-Workflow at commit 1df1a99, republished under its MIT licence (© haoyu-haoyu). 73 words, ~388 tokens.

Download SKILL.mdSave it as .claude/skills/report-generator/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
report-generator
description
Multi-AI collaborative report generator. Uses Claude for planning/writing and Gemini for diagram generation. Creates professional reports with auto-generated figures from your research content.

MAW Report Generator

Generate professional reports with auto-generated diagrams from your research content.

Features

  • Multi-AI Collaboration: Claude plans structure, Gemini generates diagrams
  • Smart Diagram Generation: Auto-detects where figures would enhance content
  • Fallback Support: Uses Mermaid diagrams when image generation is unavailable
  • Professional Output: Academic/professional style Markdown reports

Quick Start

bash
# Generate report from content
python report_generator.py --topic "My Research Topic" --content "Your research content..."

# Generate from file
python report_generator.py --topic "AI Architecture" --content-file research.txt --output report.md

# Generate single diagram
python report_generator.py --diagram-only "System architecture showing client, server, and database"

Output

  • Markdown report with sections, diagrams, and conclusion
  • Mermaid diagrams embedded (renders in GitHub, VS Code, etc.)
  • Image files when native generation available

Workflow

mermaid
graph TD
    A[Input: Research Content] --> B[Claude: Analyze & Structure]
    B --> C[Claude: Identify Diagram Needs]
    C --> D[Gemini: Generate Diagrams]
    D --> E[Claude: Write Sections]
    E --> F[Compile Final Report]
    F --> G[Output: report.md]

© haoyu-haoyu, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .maw/skills/report-generator of haoyu-haoyu/Multi-AI-Workflow.

  • SKILL.md
  • report_generator.py

Open the folder on GitHubat commit 1df1a99

Compare with similar skills

Report Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Report Generator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Report Generator this skillhaoyu-haoyu/Multi-AI-Workflow109—~388Automated safety check: PassMIT
Gemini API Devgoogle-gemini/gemini-skills4.3k—~5.1kAutomated safety check: PassApache-2.0
Gemini Live API Devgoogle-gemini/gemini-skills4.3k—~4.6kAutomated safety check: PassApache-2.0
Notebooklmroomi-fields/notebooklm-mcp192—~1.1kAutomated safety check: PassMIT
Gemini Interactions APIAyuilos/Miffan225—~4.6kAutomated safety check: PassAGPL-3.0
Gemini API Best Practicestakeshy/obsidian-gemini-helper117—~1.1kAutomated safety check: PassMIT

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Categories

Questions about Report Generator

What does Report Generator do?

Multi-AI collaborative report generator. An agent skill from haoyu-haoyu/Multi-AI-Workflow. Report Generator is an agent skill from haoyu-haoyu/Multi-AI-Workflow. Multi-AI collaborative report generator.

When should I use Report Generator?

Report Generator fits situations like: development work in your project.

How do I install Report Generator in Claude Code?

Run `npx skills add haoyu-haoyu/Multi-AI-Workflow --skill report-generator -a claude-code`. Or copy the skill folder (.maw/skills/report-generator in haoyu-haoyu/Multi-AI-Workflow) into .claude/skills/report-generator in your project. Claude Code loads it when a task matches its description.

How do I install Report Generator in Codex?

Run `npx skills add haoyu-haoyu/Multi-AI-Workflow --skill report-generator -a codex`. Or copy the skill folder (.maw/skills/report-generator in haoyu-haoyu/Multi-AI-Workflow) into .agents/skills/report-generator in your project. Codex loads it when a task matches its description.

Can I use Report Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add haoyu-haoyu/Multi-AI-Workflow --skill report-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/report-generator, .gemini/skills/report-generator, .github/skills/report-generator and .opencode/skills/report-generator in your project.

What does Report Generator need to run?

Going by SKILL.md and its folder, Report Generator needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Report Generator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Report Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Report Generator use?

Report Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Report Generator use?

About 388 tokens (SKILL.md is roughly 1.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Report Generator?

Skills that share tags, products or a category with Report Generator: Gemini API Dev (google-gemini/gemini-skills, 4.3k stars), Gemini Live API Dev (google-gemini/gemini-skills, 4.3k stars), Notebooklm (roomi-fields/notebooklm-mcp, 192 stars) and Gemini Interactions API (Ayuilos/Miffan, 225 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Report Generator?

haoyu-haoyu (a GitHub user) maintains it in haoyu-haoyu/Multi-AI-Workflow, which has 109 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on April 16, 2026.

Source: haoyu-haoyu/Multi-AI-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.