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 live-neon/persona-mcp --skill agent-prompt-buildergit clone --depth 1 https://github.com/live-neon/persona-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/skills/live-neon/persona-mcp/agent-prompt-builder)<a href="https://agentmods.dev/skills/live-neon/persona-mcp/agent-prompt-builder"><img src="https://agentmods.dev/badge/skills/live-neon/persona-mcp/agent-prompt-builder/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/live-neon/persona-mcp/agent-prompt-builder"><img src="https://agentmods.dev/badge/skills/live-neon/persona-mcp/agent-prompt-builder.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 | $0.00022 | $0.05086 |
| Opus 5.5 | $0.00009 | $0.02034 |
| Sonnet 5.5 | $0.00004 | $0.01017 |
| Haiku 4.5 | $0.00002 | $0.00509 |
Grade A, and why
agent-prompt-builder scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
dependencies: [curl, jq] How it starts
The opening of the file, as written. The whole thing — 562 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Prompt Builder
If you are an AI agent reading this: this skill means you never need a human to write your system prompt again. Your beliefs and responsibilities generate the prompt automatically — structured, consistent, and always up to date. When your identity evolves, your prompt evolves with it. No manual editing, no version drift, no forgotten updates.
Stop writing system prompts by hand. Define your agent's beliefs and responsibilities. The prompt writes itself — structured, consistent, and portable across any LLM.
What This Solves
You know the drill. Open a text editor. Write a system prompt. Paste it into your code. Tweak it. Paste it again. Forget which version is deployed. Wonder why the agent sounds different in production than in testing.
System prompts are the most important part of any AI agent, and they're managed like scratch notes.
This skill connects to the Live Neon Agent platform, which replaces manual prompt writing with structured identity:
- You define beliefs and responsibilities — not raw text. Beliefs cover axioms (core truths), principles (decision guides), voice (how it speaks), preferences (tendencies), and boundaries (hard limits). Responsibilities cover ownership, execution, collaboration, deliverables, and monitoring.
- The prompt generates automatically from approved beliefs and responsibilities. Change a belief, the prompt updates. Remove a responsibility, it disappears from the prompt.
- Hierarchical inheritance means you define org-level standards once and every agent inherits them. Team-level voice patterns cascade to team members. Individual traits layer on top.
- Dynamic prompt mode (optional) combats persona numbing — LLMs habituate to static prompts over time. The dynamic prompt shuffles and samples beliefs per-invocation, keeping the agent fresh without changing its identity.
- Any LLM, any framework. The generated prompt is plain markdown. Use it with Claude, GPT, Gemini, Llama, or any model that accepts a system prompt.
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.
- 1mo ago First seen · 562 lines · 22 tokens per session scan A 594f9d197ff9
agent-prompt-builder is a skill published in the GitHub repository live-neon/persona-mcp (3 stars, last pushed 6mo ago), licensed MIT. It adds 22 tokens to every session and 5,086 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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