Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add haoyu-haoyu/Multi-AI-Workflow --skill report-generatorgit clone --depth 1 https://github.com/haoyu-haoyu/Multi-AI-WorkflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/haoyu-haoyu/multi-ai-workflow/report-generator)<a href="https://agentmods.dev/skills/haoyu-haoyu/multi-ai-workflow/report-generator"><img src="https://agentmods.dev/badge/skills/haoyu-haoyu/multi-ai-workflow/report-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/haoyu-haoyu/multi-ai-workflow/report-generator"><img src="https://agentmods.dev/badge/skills/haoyu-haoyu/multi-ai-workflow/report-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00322 |
| Opus 5 | $0.00017 | $0.00161 |
| Sonnet 5 | $0.00007 | $0.00064 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
report-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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
# 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
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]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 47 lines · 34 tokens per session scan A d83da68d1a02
report-generator is a skill published in the GitHub repository haoyu-haoyu/Multi-AI-Workflow (109 stars, last pushed 4mo ago), licensed MIT. It adds 34 tokens to every session and 322 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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