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 skills/lgrappag/workflows-agents/analytics-user-segmentationnpx skills add LgrappaG/Workflows-Agents --skill analytics-user-segmentationgit clone --depth 1 https://github.com/LgrappaG/Workflows-AgentsWrote 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/lgrappag/workflows-agents/analytics-user-segmentation)<a href="https://agentmods.dev/skills/lgrappag/workflows-agents/analytics-user-segmentation"><img src="https://agentmods.dev/badge/skills/lgrappag/workflows-agents/analytics-user-segmentation.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 | $0.00012 | $0.00288 |
| Opus 5 | $0.00006 | $0.00144 |
| Sonnet 5 | $0.00002 | $0.00058 |
| Haiku 4.5 | $0.00001 | $0.00029 |
Grade A, and why
analytics-user-segmentation 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.
What it actually says
Analytics User Segmentation
Segment players into cohorts for analysis
Risk Level
LOW
Core Rules
- Implement properly
- Test thoroughly
- Validate results
Response Pattern
- Design appropriate approach
- Implement solution
- Test edge cases
- Validate quality
Usage Contexts
- Cohort analysis
- Development workflows
What NOT to Do
- Arbitrary segmentation
- Incomplete testing
- Deploy without validation
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.
- 3d ago First seen · 40 lines · 12 tokens per session scan A e7ef0bc866fb
analytics-user-segmentation is a skill published in the GitHub repository LgrappaG/Workflows-Agents (2 stars, last pushed 4mo ago), licensed MIT. It adds 12 tokens to every session and 288 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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