Annual Report Generator

Build a complete annual business report from raw data. Covers financial performance, operational metrics, strategic highlights, and forward-looking guidance.

3,891 stars
Complexity: easy

About this skill

This AI agent skill automates the creation of a detailed annual business report, transforming raw company data into a structured, board-ready document. It systematically covers all critical aspects of a business, including a financial summary (revenue, gross margin, EBITDA, net income), operational metrics (headcount, productivity, customer churn, NRR, CAC/LTV), a strategic review (key wins, market position, competitive landscape, risks addressed), and forward-looking guidance (next-year targets, strategic priorities, investment thesis, risk outlook). The skill is designed to streamline the laborious process of compiling annual reports, ensuring consistency and comprehensiveness. Users provide specific data points, and the agent structures them into a professional report, including an executive summary, detailed financial analysis, operational insights, and future outlook. Businesses can use this skill to quickly prepare internal reports for leadership, board meetings, or investor updates, significantly reducing the manual effort and time typically required for data aggregation and document formatting. It empowers companies to present a clear, data-driven narrative of their performance and strategic direction.

Best use case

The primary use case is to rapidly generate a professional, board-ready annual business report for internal stakeholders, investors, or strategic planning. Businesses, particularly startups, SMEs, or departments within larger organizations, benefit most by automating the aggregation and structuring of key performance indicators into a coherent narrative, saving significant time and resources.

Build a complete annual business report from raw data. Covers financial performance, operational metrics, strategic highlights, and forward-looking guidance.

Users should expect a well-structured, data-driven annual business report covering financial, operational, and strategic performance, complete with forward-looking guidance.

Practical example

Example input

Generate our annual report for 2023. Here's our data: Revenue: Q1 $1.2M, Q2 $1.5M, Q3 $1.8M, Q4 $2.1M (SaaS subscriptions, professional services). Expenses: Payroll $2M, COGS $500k, SGA $800k, R&D $600k. Customers: Start 500, End 700, Churn 8%, NRR 115%. Headcount: Start 20, End 28. Milestones: Product v2 launch Q2, Series A funding Q3.

Example output

A structured document starting with an Executive Summary (e.g., "XYZ Corp achieved 40% YoY revenue growth in 2023, driven by product innovation and market expansion."), followed by detailed Financial Performance tables and breakdowns, Operational Review metrics (customer growth, NRR, CAC/LTV), Strategic Review highlights, and Forward Guidance (e.g., "Targeting 30% revenue growth in 2024, focusing on market expansion in Europe and strategic partnerships.").

When to use this skill

  • Preparing for annual board meetings or investor updates.
  • Conducting a comprehensive internal review of business performance.
  • Needing a structured overview of financial and operational health.
  • Seeking to standardize annual reporting across departments or subsidiaries.

When not to use this skill

  • When highly sensitive or confidential data cannot be shared with an AI agent.
  • For highly customized, bespoke reports requiring specific qualitative analysis not based on structured data.
  • If the required raw data is incomplete, unstructured, or unavailable.
  • When a full audit-level report requiring human financial expert verification is mandatory.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/afrexai-annual-report/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-annual-report/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/afrexai-annual-report/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Annual Report Generator Compares

Feature / AgentAnnual Report GeneratorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

Build a complete annual business report from raw data. Covers financial performance, operational metrics, strategic highlights, and forward-looking guidance.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Annual Report Generator

Build a complete annual business report from raw data. Covers financial performance, operational metrics, strategic highlights, and forward-looking guidance.

## What This Skill Does

Takes your company data and generates a board-ready annual report with:

- **Financial Summary** — Revenue, COGS, gross margin, EBITDA, net income, YoY comparisons
- **Operational Metrics** — Headcount, productivity ratios, customer metrics, unit economics
- **Strategic Review** — Key wins, market position, competitive landscape, risks addressed
- **Forward Guidance** — Next-year targets, strategic priorities, investment thesis, risk outlook

## How to Use

Tell your agent: "Generate our annual report" and provide:

1. **Revenue figures** — Monthly or quarterly, by product/segment if available
2. **Expense data** — By category (payroll, COGS, SGA, R&D)
3. **Customer metrics** — Total customers, churn, NRR, NPS, ARR
4. **Headcount** — Start/end of year, by department
5. **Key milestones** — Product launches, partnerships, funding, market expansion

## Report Structure

### 1. Executive Summary (1 page)
- Year in review headline
- 3-5 key metrics with YoY change
- CEO/founder letter themes

### 2. Financial Performance
| Metric | This Year | Last Year | Change |
|--------|-----------|-----------|--------|
| Revenue | — | — | —% |
| Gross Margin | — | — | —pp |
| EBITDA | — | — | —% |
| Net Income | — | — | —% |
| Cash Position | — | — | — |

**Revenue breakdown** by:
- Product/service line
- Geography
- Customer segment
- New vs expansion vs renewal

**Expense analysis:**
- Cost structure breakdown (% of revenue)
- Headcount cost per employee
- R&D as % of revenue (benchmark: 15-25% for SaaS)
- SGA efficiency ratio

### 3. Operational Review
**Customer metrics:**
- Total customers (start → end)
- Logo churn rate (benchmark: <10% annually)
- Net Revenue Retention (benchmark: >110% for B2B SaaS)
- CAC and LTV with ratio (target: >3x)
- NPS or CSAT scores

**Team metrics:**
- Revenue per employee (benchmark: $200-300K for SaaS)
- Employee satisfaction/eNPS
- Turnover rate (benchmark: <15%)
- Key hires and departures

### 4. Strategic Highlights
- Top 3-5 achievements with business impact
- Product milestones and roadmap delivery
- Market expansion (new segments, geographies)
- Partnership and channel developments
- Brand and thought leadership wins

### 5. Risk Register
| Risk | Likelihood | Impact | Mitigation | Status |
|------|-----------|--------|------------|--------|
| Market contraction | Medium | High | Diversified segments | Monitoring |
| Key person dependency | Medium | High | Cross-training program | In progress |
| Competitive pressure | High | Medium | Innovation velocity | Active |

### 6. Forward Guidance
- Revenue target and growth assumptions
- Key initiatives for next year (max 5)
- Planned investments (headcount, product, market)
- Metrics to watch
- Scenarios: bear / base / bull

## Benchmarks by Company Stage

| Stage | Revenue Growth | Burn Multiple | Rule of 40 |
|-------|---------------|---------------|------------|
| Seed–A | 100-300% | <2x | N/A |
| Series B | 80-150% | <1.5x | >20 |
| Series C | 50-80% | <1x | >30 |
| Growth | 30-50% | <0.8x | >40 |
| Scale | 20-30% | Profitable | >40 |

## Presentation Tips

- **Lead with the story, support with numbers** — Don't dump data. Frame each section around a narrative.
- **Honest about misses** — Credibility comes from acknowledging what didn't work.
- **Forward-looking > backward-looking** — Investors care more about where you're going.
- **Consistent formatting** — Same metrics, same definitions, year over year.
- **One page per section** — Force prioritization. If it doesn't fit one page, it's not tight enough.

## Useful Formulas

```
Gross Margin = (Revenue - COGS) / Revenue
EBITDA Margin = EBITDA / Revenue
Rule of 40 = Revenue Growth % + EBITDA Margin %
Burn Multiple = Net Burn / Net New ARR
Magic Number = Net New ARR / Prior Quarter S&M Spend
CAC Payback = CAC / (ARPA × Gross Margin)
LTV = ARPA × Gross Margin / Monthly Churn Rate
```

---

Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI context packs that make your agents actually useful.

**Get the full toolkit:**
- [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find where you're losing money
- [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Deploy your first AI agent in 15 minutes
- [Context Packs Store](https://afrexai-cto.github.io/context-packs/) — Industry-specific agent intelligence ($47/pack)

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