Pine Backtester
TradersPost/pinescript-agents
Implements comprehensive backtesting and performance metrics.
Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks.
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install JoelLewis/finance_skills advisor-dashboards --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .claude/skills/advisor-dashboards && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .claude/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboardsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install JoelLewis/finance_skills advisor-dashboards --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .agents/skills/advisor-dashboards && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .agents/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install JoelLewis/finance_skills advisor-dashboards --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .cursor/skills/advisor-dashboards && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .cursor/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/JoelLewis/finance_skills.git --path plugins/advisory-practice/skills/advisor-dashboards--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install JoelLewis/finance_skills advisor-dashboards --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .gemini/skills/advisor-dashboards && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .gemini/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install JoelLewis/finance_skills advisor-dashboardsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .github/skills/advisor-dashboards && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .github/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install JoelLewis/finance_skills advisor-dashboards --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JoelLewis/finance_skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/advisory-practice/skills/advisor-dashboards .opencode/skills/advisor-dashboards && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "advisor-dashboards" agent skill from https://github.com/JoelLewis/finance_skills/tree/main/plugins/advisory-practice/skills/advisor-dashboards into .opencode/skills/advisor-dashboards/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "advisor-dashboards", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
advisor-dashboardsDesign, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks.
Advisor Dashboards is an agent skill from JoelLewis/finance_skills. Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks. Use when the user asks about tracking firm-level metrics, monitoring advisor productivity, measuring organic growth rate, analyzing client retention and attrition, building executive or branch manager views, setting up exception alerts for NIGO and operational items, benchmarking against industry peers, or designing role-based dashboard access. Also trigger when users mention 'how is the…
Its SKILL.md is about 7.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/examples.md`).
It sits in Business, Finance & HR, covering OKRs and executive reporting and Authorization and RBAC. The repository describes itself as: Claude Code skill plugins for financial services — 81 skills across 7 domain plugins covering investment management, compliance, advisory practice, trading, and operations. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 5c498ea. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Advisor Dashboards loads about 7.2k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 178 tokens; SKILL.md has 3,803 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from JoelLewis/finance_skills at commit 5c498ea, republished under its MIT licence (© JoelLewis). 3,803 words, ~7,229 tokens.
.claude/skills/advisor-dashboards/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.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.
Average Account Size. Total AUM divided by the number of accounts (or households). Tracked over time, this metric reveals whether the firm is attracting larger or smaller relationships. When combined with revenue per client, it exposes effective fee rate trends at the client level.
Organic Growth Rate. Net new assets (new client assets plus existing client contributions minus withdrawals minus terminated client assets) divided by beginning-of-period AUM, expressed as an annualized percentage. Organic growth strips out market appreciation to isolate the advisor-driven component of AUM change. Industry benchmarks for healthy RIAs typically target 5-10% annual organic growth. Negative organic growth — even during strong markets — signals that the firm is losing ground despite favorable conditions.
Retention Rate. The percentage of beginning-of-period AUM or client count that remains at the end of the period, excluding market effects. A 95% client retention rate means 5% of clients (by count or AUM) left during the period. Retention is often more valuable than acquisition: replacing a departed $2M client requires acquiring two new $1M clients, each carrying acquisition cost and onboarding effort.
Referral Rate. New clients acquired through existing client referrals as a percentage of total new clients. Referral-sourced clients tend to have higher AUM, lower acquisition cost, and higher retention. Tracking referral rate by advisor identifies which advisors have the strongest referral networks and which may benefit from referral training or process improvement.
Profitability Metrics. For firms that track practice-level financials, operating margin (revenue minus direct and allocated expenses, divided by revenue) is the ultimate measure of practice efficiency. Industry benchmarks for well-run RIAs typically show operating margins of 25-35%. Revenue per employee (total revenue divided by total headcount) provides a simpler proxy for overall productivity. Compensation-to-revenue ratio (total compensation including advisor payouts divided by total revenue) should typically fall between 55-70% for sustainable practices.
AUM and revenue dashboards provide the financial pulse of the advisory practice. They answer the questions firm leadership asks most frequently: how much do we manage, how much are we earning, where is the growth coming from, and what does the trajectory look like?
AUM by Advisor/Team/Segment. A hierarchical view that drills from firm total AUM down to team, advisor, and individual household. Heatmaps or bar charts comparing advisors by AUM highlight concentration risk (if one advisor manages a disproportionate share) and identify capacity constraints (advisors approaching their effective management limit). Segment views (by client tier, account type, or investment model) reveal the composition of the firm's book and inform strategic decisions about target markets.
Revenue by Fee Type. A breakdown showing what percentage of total revenue comes from AUM-based fees versus planning fees, hourly fees, or other sources. Firms diversifying beyond pure AUM-based revenue should track the mix over time. A rising share of planning fee revenue indicates successful adoption of comprehensive planning services. Billing exception rates by fee type highlight operational trouble spots.
Pipeline and Flows Tracking. The flow of assets into and out of the firm, tracked on a rolling basis. Key flow metrics include:
AUM Growth Decomposition. A waterfall chart or stacked bar showing the components of AUM change over a period:
This decomposition is essential for management because it separates controllable growth (net new assets) from uncontrollable growth (market returns). A firm whose AUM grew 12% in a year where markets returned 10% actually achieved only 2% organic growth — a far less impressive result than the headline number suggests.
Client flow analytics go beyond aggregate flow numbers to analyze the dynamics of client acquisition, retention, and asset consolidation at a granular level.
New Client Acquisition Funnel. Track the conversion pipeline from initial lead through prospect meeting, proposal delivery, agreement signing, and account funding. Key funnel metrics include: lead-to-meeting conversion rate, meeting-to-proposal rate, proposal-to-close rate, close-to-fund rate, average time from lead to funded account, and average funded amount versus initial estimate. Funnel analytics by advisor expose differences in prospecting effectiveness and identify bottlenecks (an advisor with a high meeting-to-proposal rate but low proposal-to-close rate may need help with proposal quality or pricing).
Client Attrition Tracking. Monitor departing clients by reason (voluntary termination, death, relocation, fee sensitivity, service dissatisfaction, competitor solicitation), by advisor, by client segment, and by tenure. Attrition dashboards should display both the count and the AUM impact of departures. Early-tenure attrition (clients leaving within the first two years) suggests onboarding or expectation-setting issues. Long-tenure attrition (clients of 10+ years departing) may signal relationship fatigue or a generational transition where heirs move assets.
Money-in-Motion Indicators. Proactive signals that a client may be consolidating assets (opportunity) or preparing to leave (risk). Key indicators include: large cash deposits from external sources (potential rollover or inheritance), systematic outflows exceeding income needs (possible transfer to a competitor), reduced engagement (fewer meetings, unanswered communications), and changes to beneficiary designations or account titling. The dashboard should flag these indicators for advisor follow-up before the client makes a final decision.
Asset Consolidation Tracking. For existing clients with held-away assets, track consolidation opportunities — the gap between total household assets (visible through aggregation) and managed assets. A client with $3M managed and $2M held away in a former employer 401(k) represents a $2M consolidation opportunity. Consolidation dashboards rank opportunities by dollar value and likelihood, enabling advisors to prioritize outreach.
Competitive Losses. When clients depart, capture the destination (self-directed, competitor RIA, wirehouse, robo-advisor, bank) and the stated reason. Over time, this data reveals competitive threats and informs the firm's value proposition and pricing strategy. A cluster of departures to a lower-cost competitor signals fee pressure; departures to a full-service wirehouse may indicate that clients want services the firm does not offer.
Generational Transfer Tracking. A growing concern for advisory firms is the risk that heirs of deceased clients move inherited assets elsewhere. Track accounts where the primary account holder is over age 75, the estimated intergenerational transfer value, whether the firm has an established relationship with the next generation, and the outcome of recent inheritance events (assets retained vs. assets departed). Firms that proactively engage the next generation retain significantly more inherited assets than those that wait until the triggering event occurs.
Exception dashboards surface items that require immediate attention — anomalies, breaches, overdue tasks, and operational failures that deviate from expected norms. These dashboards are typically used by operations managers, compliance officers, and practice managers rather than individual advisors.
Compliance Alerts. Items requiring compliance attention: overdue annual reviews, stale client profiles, unsigned disclosures, advertising items awaiting review, trade pre-clearance violations, outside business activity disclosures due, gift and entertainment reporting gaps, and code of ethics certification deadlines. Each alert should display the responsible party, the deadline, days until (or past) the deadline, and the escalation status. Color coding (green/yellow/red) provides an at-a-glance severity assessment.
Operational Exceptions. Reconciliation breaks between the PMS and custodian, failed data feeds, NIGO (not in good order) account opening documents, incomplete account transfers (ACAT failures), unsigned paperwork, and pending account maintenance requests. The dashboard should display exception age (how long the item has been open) and flag items that have exceeded their service-level agreement.
Rebalancing Drift Alerts. Accounts where portfolio drift exceeds the firm's threshold but rebalancing has not been initiated. Display the client name, account, current allocation versus target, magnitude of drift, days since threshold breach, and assigned advisor. Persistent drift alerts may indicate advisor inattention or intentional deviation that requires documentation.
Billing Exceptions. Accounts with unusual billing outcomes: fees significantly higher or lower than the prior period, zero-dollar fees, negative fee calculations, accounts missing from the billing run, fee-schedule mismatches (the rate charged differs from the assigned schedule), and overdue invoice payments. Billing exception dashboards should be reviewed before every billing run approval.
Custodian NIGO Status. A centralized view of account opening and maintenance requests that have been returned as "not in good order" by the custodian. NIGO items delay account funding and create a poor client experience. The dashboard should track NIGO reason (missing signature, incorrect form version, incomplete information), age, assigned CSA, and resolution status.
Pending Tasks and Aging. A consolidated view of all open tasks across the practice — from NBA-recommended actions and CRM tasks to operational work items and compliance deadlines. Group by responsible party, sort by age, and flag items approaching or exceeding their SLA. Aging analysis (average days to resolve by task type) identifies process bottlenecks and staffing constraints.
Productivity dashboards help practice managers and firm leadership understand how effectively advisors are using their time and where capacity exists for growth.
Clients Per Advisor. The number of active client households assigned to each advisor. Industry data suggests that a solo advisor can effectively manage 75-125 households depending on service model complexity and support staff. Advisors approaching their capacity limit need either additional support staff, a service model adjustment, or a planned transition of smaller clients. Advisors well below capacity represent either growth potential or an underperformance concern.
Revenue Per Advisor. Total advisory revenue generated per advisor, calculated both as the advisor's personal book revenue and as revenue per advisor adjusted for team support (dividing team revenue by the number of team members). Revenue per advisor benchmarked against current industry surveys (e.g., the Schwab RIA Benchmarking Study and major adviser compensation and staffing studies — verify the current editions, as study names and sponsors change) reveals whether the firm's advisor economics are competitive.
Meeting Volume. The number of client meetings (in-person, video, phone) conducted per advisor per period, sourced from CRM activity logs or calendar integration. Meeting volume is a leading indicator of relationship health and prospecting activity. Advisors with declining meeting counts may be disengaging from proactive client management.
Proposal-to-Close Ratio. The percentage of formal proposals or financial plans delivered that result in a signed advisory agreement and funded account. This metric, sourced from CRM pipeline data, measures advisor effectiveness at converting prospects into clients. Low ratios may indicate pricing issues, proposal quality problems, or a mismatch between the firm's value proposition and the prospect's needs.
Onboarding Pipeline. New clients in various stages of the onboarding process — from signed agreement through account opening, asset transfer, initial investment, and first review meeting. Bottlenecks in the onboarding pipeline (e.g., transfers taking 30+ days) create client dissatisfaction and delay revenue recognition. Track average onboarding time and identify the stage where delays most commonly occur.
Capacity Planning. A forward-looking view that combines current client count, revenue per client, and projected growth to estimate when each advisor will reach capacity. Capacity planning dashboards inform hiring decisions, team restructuring, and client assignment strategies. A firm projecting that three advisors will hit capacity within 12 months should begin recruiting and training before capacity becomes a constraint.
Dashboard effectiveness depends as much on design and delivery as on the underlying data. A technically accurate dashboard that no one uses provides zero value.
Role-Based Views. Different roles need different information:
Drill-Down from Summary to Detail. Every summary metric should be clickable, allowing the user to drill from the firm-level number down to the team, advisor, client, and account level. An executive who sees that net flows turned negative this quarter should be able to click through to see which advisors experienced outflows, which clients departed, and what reasons were recorded. Without drill-down capability, dashboards generate questions but do not answer them.
Real-Time vs. Batch Refresh. Not all metrics require real-time data. AUM and performance figures depend on end-of-day custodian feeds and should refresh overnight. Exception dashboards benefit from intraday refresh (especially compliance and operational alerts). Pipeline and flow data depend on CRM updates and are typically current as of the last advisor entry. Clearly label the data freshness on every dashboard panel so users understand whether they are seeing today's data or yesterday's close.
Mobile-First Design. Advisors spend significant time outside the office — at client meetings, conferences, and working remotely. Dashboards must function on tablet and phone screens. Mobile design requires ruthless prioritization: show only the top 3-5 metrics on the mobile view, with the option to expand. Push notifications for critical alerts (compliance deadlines, large cash movements, billing exceptions) ensure that time-sensitive items reach the advisor regardless of whether they are at their desk.
Data Source Integration. Advisory dashboards pull data from multiple systems: the portfolio management system (AUM, positions, performance, drift), CRM (client data, activities, pipeline, tasks), billing engine (revenue, fee analytics, exceptions), custodian feeds (account status, NIGO, transfers), financial planning tools (plan status, funded ratios), and compliance systems (review tracking, surveillance). Dashboard architecture must include a data integration layer — whether a data warehouse, an ETL pipeline, or direct API connections — that normalizes and reconciles data from these disparate sources into a single consistent view.
Dashboards become significantly more valuable when metrics are displayed alongside benchmarks and goals, providing context that transforms raw numbers into performance assessments.
Firm-Level Targets. Annual and quarterly targets set by firm leadership for key metrics: total AUM, organic growth rate, revenue, revenue growth, net new clients, retention rate, and profitability. Display actual performance against targets with a simple actual/target/variance format and a progress bar or gauge. Color code based on whether the firm is on track (green), at risk (yellow), or behind (red) based on year-to-date run rate.
Advisor-Level Goals. Individual goals negotiated between each advisor and firm management. Common advisor-level goals include: net new AUM gathered, new households acquired, revenue target, meeting count, and planning engagement conversions. Advisor goal dashboards should be visible to the individual advisor (for self-management) and to the practice manager (for coaching and accountability). Display goals with the same actual/target/variance format and include a trend line showing progress over time.
Industry Benchmarks for RIA Metrics. Annual benchmarking studies published by major custodians and industry publishers — e.g., the Schwab RIA Benchmarking Study and Fidelity's RIA benchmarking research — provide median and top-quartile figures for key RIA metrics: revenue per advisor, AUM per advisor, operating margin, clients per advisor, staff-to-advisor ratio, organic growth rate, and client retention rate. Displaying firm metrics alongside these industry benchmarks reveals whether the firm is performing at, above, or below peer levels. Benchmarking is most meaningful when filtered by firm size (AUM range), geography, and service model to ensure an apples-to-apples comparison. Benchmarking studies are periodically renamed, merged, or discontinued, so verify the current edition before citing specific figures.
Trend Analysis. Every KPI should be displayed with at least 8-12 quarters of historical trend data. Trends reveal patterns that point-in-time snapshots miss: gradual fee compression (effective fee rate declining 2 bps per year), seasonal flow patterns (outflows spike in April for tax payments), or advisor capacity approaching saturation (clients per advisor rising steadily). Moving averages (3-quarter or 4-quarter) smooth volatility and make the underlying trend more visible.
Three worked examples are in references/examples.md — load for an end-to-end scenario: (1) building a four-quadrant executive dashboard for an RIA management committee, (2) designing an advisor-facing daily dashboard with a prioritized action queue, (3) creating an exception monitoring dashboard for an operations team with SLA-based aging.
© JoelLewis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in plugins/advisory-practice/skills/advisor-dashboards of JoelLewis/finance_skills.
Open the folder on GitHubat commit 5c498ea
Advisor Dashboards next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Advisor Dashboards this skillJoelLewis/finance_skills | 206 | — | ~7.2k | Automated safety check: Pass | MIT | |
| Pine BacktesterTradersPost/pinescript-agents | 170 | 1 repos | ~3.9k | Automated safety check: Pass | None | |
| Analytics Strategyrampstackco/claude-skills | 945 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Onboarding Plannerbpinheiroms/dotfiles | 108 | — | ~5.4k | Automated safety check: Pass | None | |
| Replit Decksanqiufong/slides-from-anything | 132 | 1 repos | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Building Streamlit Dashboardsiusztinpaul/designing-real-world-ai-agents-workshop | 512 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
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Categories
Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks. Advisor Dashboards is an agent skill from JoelLewis/finance_skills. Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks.
Advisor Dashboards fits situations like: the user asks about tracking firm-level metrics; monitoring advisor productivity; measuring organic growth rate; analyzing client retention and attrition.
Run `npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a claude-code`. Or copy the skill folder (plugins/advisory-practice/skills/advisor-dashboards in JoelLewis/finance_skills) into .claude/skills/advisor-dashboards in your project. Claude Code loads it when a task matches its description.
Run `npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a codex`. Or copy the skill folder (plugins/advisory-practice/skills/advisor-dashboards in JoelLewis/finance_skills) into .agents/skills/advisor-dashboards in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add JoelLewis/finance_skills --skill advisor-dashboards -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/advisor-dashboards, .gemini/skills/advisor-dashboards, .github/skills/advisor-dashboards and .opencode/skills/advisor-dashboards in your project.
SKILL.md names no scripts, command-line tools or credentials: Advisor Dashboards is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Advisor Dashboards is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 7.2k tokens (SKILL.md is roughly 29k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Advisor Dashboards: Pine Backtester (TradersPost/pinescript-agents, 170 stars), Analytics Strategy (rampstackco/claude-skills, 945 stars), Onboarding Planner (bpinheiroms/dotfiles, 108 stars) and Replit Deck (sanqiufong/slides-from-anything, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
JoelLewis (a GitHub user) maintains it in JoelLewis/finance_skills, which has 206 GitHub stars. The repository holds 91 skills in this directory. The repository was last updated on July 18, 2026.
Source: JoelLewis/finance_skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.