user-segmentation-profiler

A set of rules for classifying a user into a beginner, builder or growth group based on their experience, limits and goals.

In plain words
What is it for?
Use it to identify a user’s experience level and needs when planning how to support or communicate with them.
Why use it?
It provides a consistent way to decide which type of user you are dealing with.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/maxkmet/idea-validation-agents/user-segmentation-profiler
Clone the repo
git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents

Made for: Cursor.

Per session 34 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 76 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00034 $0.00076
Opus 5 $0.00017 $0.00038
Sonnet 5 $0.00007 $0.00015
Haiku 4.5 $0.00003 $0.00008

Measured 3d ago against content hash 1a0a580fd398, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

user-segmentation-profiler 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 3d 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.

.cursor/rules/user-segmentation-profiler.mdc · 7 lines

What it actually says

See skills/user-segmentation-profiler/SKILL.md for full instructions and output schema.

Changes

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.

  1. 3d ago First seen · 7 lines · 34 tokens per session scan A 1a0a580fd398

Subscribe to this mod's changes

user-segmentation-profiler is a cursor rule published in the GitHub repository MaxKmet/idea-validation-agents (448 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 76 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.