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 advisor-dashboardsgit 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/advisor-dashboards)<a href="https://agentmods.dev/skills/joellewis/finance_skills/advisor-dashboards"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/advisor-dashboards/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/advisor-dashboards"><img src="https://agentmods.dev/badge/skills/joellewis/finance_skills/advisor-dashboards.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 | $0.00134 | $0.05360 |
| Opus 5 | $0.00067 | $0.02680 |
| Sonnet 5 | $0.00027 | $0.01072 |
| Haiku 4.5 | $0.00013 | $0.00536 |
Grade A, and why
advisor-dashboards 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 13d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advisor Dashboards
Core Concepts
1. Practice-Level KPIs
Key performance indicators for advisory practices fall into several categories, each measuring a different dimension of firm health. A well-designed KPI framework provides both a snapshot of current performance and the trend data needed to identify emerging risks or opportunities.
AUM (Assets Under Management). The foundational metric for any AUM-based advisory practice. Total firm AUM is the product of client count, average relationship size, and market performance. AUM should be tracked at multiple levels: firm total, by advisor or team, by client segment (high-net-worth, mass affluent, institutional), by account type (taxable, IRA, trust, plan), and by custodian. AUM changes decompose into two components — market appreciation/depreciation and net new assets — and tracking each separately reveals whether growth is organic (advisor-driven) or market-driven.
Revenue. Total advisory revenue, broken down by fee type (AUM-based fees, financial planning fees, hourly fees, performance fees, other), by advisor or team, by client segment, and by billing period. The effective fee rate (total revenue divided by average AUM) is a critical derived metric that reveals fee compression trends over time. Revenue should be tracked on both an accrual basis (for GAAP reporting) and a cash basis (for cash flow management).
Client Count. The number of active client households, tracked by segment, advisor, and tenure. Distinguish between households (the billing and relationship unit) and accounts (the custodial unit). A firm with 500 households might have 2,000 accounts. Client count trends — net new households per quarter, attrition rate, and average household tenure — reveal the health of the firm's client acquisition and retention efforts.
Revenue Per Client. Average annual revenue per household, segmented by client tier. This metric exposes whether the firm is growing revenue through larger relationships or by adding many small ones. Declining revenue per client may indicate fee compression, client downsizing, or an acquisition strategy that targets smaller relationships than the firm's economics require.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 163 lines · 134 tokens per session scan A b3eaba7f80a8
advisor-dashboards is a skill published in the GitHub repository JoelLewis/finance_skills (184 stars, last pushed 1mo ago), licensed MIT. It adds 134 tokens to every session and 5,360 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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