Client Report logo

Client Report

OrganizationPopular
anthropics
client-report

Generate professional client-facing performance reports with portfolio returns, allocation breakdowns, and market commentary. Suitable for quarterly or annual distribution. Triggers on "client report", "performance report", "quarterly report for [client]", "generate reports", or "client statement".

Overview

Publisheranthropics
Repositoryfinancial-services
Skill nameclient-report
Stars
38.4K
Forks
5.5K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Client Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/meeting-prep-agent/skills/client-report
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/financial-services.git /tmp/financial-services
mkdir -p .claude/skills
cp -r /tmp/financial-services/plugins/agent-plugins/meeting-prep-agent/skills/client-report .claude/skills/client-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Client Report in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Client Report on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Client Report is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Client Report

Workflow

Step 1: Report Parameters

  • Client name and household
  • Reporting period: Quarter, YTD, annual, custom range
  • Accounts: All accounts or specific account
  • Benchmark: S&P 500, 60/40 blend, custom benchmark matching IPS
  • Firm branding: Logo, colors, disclaimers

Step 2: Performance Summary

Household Summary:

QTDYTD1-Year3-Year Ann.5-Year Ann.ITD Ann.
Portfolio
Benchmark
+/-

By Account:

AccountTypeValueQTDYTDBenchmark
Joint TaxableBrokerage
John IRATraditional
Jane RothRoth IRA
529 PlanEducation
Total

Step 3: Allocation Overview

Current allocation with visual (pie chart or bar chart):

Asset Class% of Portfolio$ ValueBenchmark %

Step 4: Holdings Detail

SecurityAsset ClassSharesPriceValue% of PortfolioQTD Return

Step 5: Market Commentary

Brief market summary tailored to the client's level of sophistication:

  • What happened in markets this quarter (2-3 sentences)
  • How it affected the portfolio
  • Outlook and positioning rationale (2-3 sentences)
  • No jargon for retail clients; can be more technical for sophisticated investors

Step 6: Activity Summary

  • Trades executed during the period
  • Contributions and withdrawals
  • Dividends and interest received
  • Fees charged
  • Rebalancing activity

Step 7: Planning Notes

  • Progress toward financial goals (retirement, education, etc.)
  • Any plan changes or recommendations
  • Upcoming action items
  • Next review date

Step 8: Output

  • PDF report (8-12 pages) with firm branding
  • Word document for customization
  • Excel data appendix (optional)

Report Structure:

  1. Cover page (client name, period, firm logo)
  2. Executive summary (1 page)
  3. Performance summary (1-2 pages)
  4. Allocation overview with charts (1 page)
  5. Holdings detail (1-2 pages)
  6. Market commentary (1 page)
  7. Activity summary (1 page)
  8. Planning notes (1 page)
  9. Disclosures and disclaimers (1 page)

Important Notes

  • Performance must be calculated net of fees unless client/compliance requires gross
  • Always include appropriate disclaimers and disclosures (past performance, risk factors)
  • Reports should be consistent across clients — use a standard template
  • Match the level of detail to the client — some want every holding, others want a one-page summary
  • Benchmark selection matters — use the benchmark from the IPS, not whatever looks best
  • Review for compliance approval before first distribution of a new template

Frequently asked questions

What does the Client Report AI skill do?

Generate professional client-facing performance reports with portfolio returns, allocation breakdowns, and market commentary. Suitable for quarterly or annual distribution. Triggers on "client report", "performance report", "quarterly report for [client]", "generate reports", or "client statement".

Why use Client Report on TypingMind?

Because you install it once and use it with any model. Client Report is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Client Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/financial-services/tree/main/plugins/agent-plugins/meeting-prep-agent/skills/client-report. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Client Report?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Client Report?

As many as you like. As long as a model supports skills, you can use Client Report with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Client Report AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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