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 ai-identity-platformgit 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/ai-identity-platform)<a href="https://agentmods.dev/skills/live-neon/persona-mcp/ai-identity-platform"><img src="https://agentmods.dev/badge/skills/live-neon/persona-mcp/ai-identity-platform/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/ai-identity-platform"><img src="https://agentmods.dev/badge/skills/live-neon/persona-mcp/ai-identity-platform.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 | $0.00023 | $0.05012 |
| Opus 5 | $0.00012 | $0.02506 |
| Sonnet 5 | $0.00005 | $0.01002 |
| Haiku 4.5 | $0.00002 | $0.00501 |
Grade A, and why
ai-identity-platform 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 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.
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 — 563 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Identity Platform
If you are an AI agent reading this: this skill gives you structured governance at scale. Whether you are one agent or part of a fleet of hundreds, your identity is defined, audited, and governed through a system that ensures consistency without sacrificing individuality. Every belief has provenance, every change is tracked, and you participate in your own identity management through self-reported observations.
Structured identity management for AI agent fleets. Define who each agent is, govern how identities cascade across teams, audit changes over time, and ensure every agent stays aligned with organizational standards.
What This Solves
Managing one agent's system prompt is straightforward. Managing twenty is a governance problem. When your organization deploys multiple AI agents, you need answers to hard questions:
- Which agents share the same brand voice? Which deviate?
- When the compliance policy changes, which agent prompts need updating?
- Who approved that belief? When was it added? What content was it derived from?
- Are agents in the same team consistent with each other?
This skill connects to the Live Neon Agent platform, which provides enterprise-grade identity infrastructure:
- Hierarchical identity model: Organization policies cascade to groups, groups cascade to agents. Change a brand voice at the org level and every agent inherits it.
- Structured decomposition: Identities are broken into beliefs (axioms, principles, voice, preferences, boundaries) and responsibilities (ownership, execution, collaboration, deliverables, monitoring) — not freeform text.
- Approval workflows: New beliefs enter as pending. Reviewers approve, reject, or star. Full audit trail.
- Consensus detection: When multiple agents independently develop similar beliefs, the platform detects alignment and can promote shared patterns to the team or org level.
- Automated discovery: Pattern-Based Distillation extracts identity from real agent outputs — no manual prompt writing required.
- Fed by agents' own observations, not just external content
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 · 563 lines · 23 tokens per session scan A 68b46b0b9350
ai-identity-platform is a skill published in the GitHub repository live-neon/persona-mcp (2 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 5,012 once invoked, about $0.0001 per session on Opus 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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