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 JoelLewis/finance_skills --skill crm-client-lifecyclegit clone --depth 1 https://github.com/JoelLewis/finance_skillsWrote 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/joellewis/finance_skills/crm-client-lifecycle)<a href="https://agentmods.dev/skills/joellewis/finance_skills/crm-client-lifecycle"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/crm-client-lifecycle/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/joellewis/finance_skills/crm-client-lifecycle"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/crm-client-lifecycle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00140 | $0.06407 |
| Opus 5 | $0.00070 | $0.03204 |
| Sonnet 5 | $0.00028 | $0.01281 |
| Haiku 4.5 | $0.00014 | $0.00641 |
Grade A, and why
crm-client-lifecycle 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRM & Client Lifecycle
Core Concepts
Client Segmentation Models
Client segmentation assigns every household to a category that determines the level of service, contact frequency, review cadence, and resource allocation the firm provides. Without systematic segmentation, advisors default to reactive service — responding to whoever calls — rather than proactive, tiered engagement that matches effort to relationship value.
AUM-based segmentation is the most common starting point. A typical three-tier model:
| Tier | Household AUM | Typical Label |
|---|---|---|
| A | $2,000,000+ | Platinum |
| B | $500,000 - $1,999,999 | Gold |
| C | Under $500,000 | Silver |
AUM-based segmentation is simple to implement because AUM data is readily available from the custodian or portfolio management system. However, AUM alone is an incomplete measure of relationship value.
Revenue-based segmentation uses total annual fees generated by the household rather than asset levels. This captures value more accurately when fee schedules vary across clients, when some households pay financial planning fees in addition to AUM fees, or when clients have complex billing arrangements. Revenue data comes from the billing system and should be annualized to smooth quarterly fluctuations.
Multi-factor segmentation combines quantitative and qualitative dimensions for a more complete picture:
- Assets under management (current relationship size)
- Revenue generated (actual economic value to the firm)
- Growth potential (age, career trajectory, expected inheritances, held-away assets not yet consolidated)
- Referral activity (clients who actively refer new prospects)
- Relationship depth (number of services engaged — investment management, financial planning, tax planning, estate planning, insurance)
- Strategic importance (centers of influence, professional advisors who refer, board members, community leaders)
Behavioral segmentation classifies clients by engagement patterns rather than dollar amounts. Categories might include: highly engaged (frequent contact, attends events, uses the client portal), moderately engaged (responds to outreach, attends annual reviews), passively engaged (minimal contact, rarely initiates), and disengaged (does not respond to outreach, skips reviews). Behavioral segmentation identifies retention risk and helps advisors tailor their communication approach.
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.
- 10d ago First seen · 244 lines · 140 tokens per session scan A baf933456372
crm-client-lifecycle is a skill published in the GitHub repository JoelLewis/finance_skills (184 stars, last pushed 1mo ago), licensed MIT. It adds 140 tokens to every session and 6,407 once invoked, about $0.0007 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.
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