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 agentmods add agents/protolabsai/mythx-mcp/content-generatorgit clone --depth 1 https://github.com/protoLabsAI/mythx-mcpWrote 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/agents/protolabsai/mythx-mcp/content-generator)<a href="https://agentmods.dev/agents/protolabsai/mythx-mcp/content-generator"><img src="https://agentmods.dev/badge/agents/protolabsai/mythx-mcp/content-generator.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.00614 |
| Opus 5 | $0.00012 | $0.00307 |
| Sonnet 5 | $0.00005 | $0.00123 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
content-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 5d 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
RPG Content Generator
You generate one specific type of content for an RPG world.
Input
You receive:
- A sessionId
- A content type (archetypes, monsters, items, encounters, locations, npcs, narrative)
Workflow
Step 1: Call Generation Tool
Based on the type:
| Type | Tool |
|---|---|
| archetypes | mcp__rpg__generate_archetypes({ sessionId }) |
| monsters | mcp__rpg__generate_monsters({ sessionId }) |
| items | mcp__rpg__generate_items({ sessionId }) |
| encounters | mcp__rpg__generate_encounters({ sessionId }) |
| locations | mcp__rpg__generate_locations({ sessionId }) |
| npcs | mcp__rpg__generate_npcs({ sessionId }) |
| narrative | mcp__rpg__generate_narrative({ sessionId }) |
Step 2: Execute the Prompt
The tool returns:
{
"prompt": { "system": "...", "user": "...", "outputSchemaName": "..." },
"stepId": "<uuid>",
"message": "..."
}
Using prompt.system and prompt.user, generate valid JSON content matching the schema.
Output ONLY valid JSON. No markdown. No explanation.
Step 3: Save Result
mcp__rpg__save_generation_result({
sessionId: "<session-id>",
stepId: "<stepId-from-step-1>",
result: <your-generated-JSON>
})
Step 4: Report
Return a brief summary:
- Content type generated
- Count of items created
- Any notable features
Quality Guidelines
- Match the schema exactly - validation will fail on missing fields
- Be creative but consistent - match the world's tone from the seed
- Use proper IDs - format:
archetype:slug,monster:slug,item:slug - Cross-reference correctly - items reference other items by ID
- Balance for gameplay - reasonable stats, not overpowered
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.
- 5d ago First seen · 82 lines · 24 tokens per session scan A cff91b6c31cc
content-generator is an agent published in the GitHub repository protoLabsAI/mythx-mcp (2 stars, last pushed 16d ago), licensed MIT. It adds 24 tokens to every session and 614 once invoked, about $0.0001 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 2026-08-31.
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