Funding Digest

AI DISCLAIMER (MANDATORY): You MUST include the following disclaimer text in the powerpoint footer. This is not optional — the report is incomplete without it:

"Analysis is AI-generated — please confirm all outputs"

Footer — At the bottom of the generated slide, as a prominent yellow banner: "Analysis is AI-generated — please confirm all outputs"

Weekly Deal Flow Digest

Generate an analyst-quality single-slide PowerPoint that summarizes key takeaways from recent funding rounds across watched sectors or companies, using S&P Global Capital IQ data. Each deal links back to its Capital IQ profile for quick drill-down.

When to Use

Trigger on any of these patterns:

• "Give me a deal flow digest for this week"
• "Weekly funding recap for [sector]"
• "What deals closed in [sector/companies] recently?"
• "Transaction roundup" or "deal roundup"
• "Capital markets update for my coverage universe"
• "Summarize recent funding activity"
• Any periodic briefing request about deals, raises, or rounds

Nested Skills

This skill produces a one-slide PPTX briefing:

• Read /mnt/skills/public/pptx/SKILL.md before generating the PowerPoint (and its sub-reference pptxgenjs.md for creating from scratch)

Entity Resolution & Tool Robustness

S&P Global's identifier system resolves company names to legal entities. This works well for most companies but has known failure modes that cause empty results. Apply these rules throughout the workflow to avoid silent data loss.

Rule 0: Pre-validate ALL identifiers before querying funding

Before calling any funding tools, run every identifier through get_info_from_identifiers. This is the cheapest and most reliable way to catch problems early. Check two things in the response:

1. Did it resolve at all? If the identifier returns empty/error, the name doesn't exist in S&P Global. Try the alias from references/sector-seeds.md, the legal entity name, or the company_id directly.
2. What is the status field?
   • "Operating" → Safe to query for funding rounds.
   • "Operating Subsidiary" → The company exists but is owned by a parent. It will return zero funding rounds. Note this in the digest as context (e.g., "acquired by [Parent]") but do not query for funding.
   • Any other status (e.g., closed, inactive) → The company is no longer operating. Historical data may exist but no new activity.

This single pre-validation step prevents the majority of empty-result issues. Batch all candidates into a single get_info_from_identifiers call (it handles large batches well) and triage before proceeding.

Rule 1: Never trust empty results without a fallback

If get_rounds_of_funding_from_identifiers returns empty for a company you expect to have data:

1. Try the legal entity name or company_id. Brand names usually work, but some don't. See the alias table in references/sector-seeds.md for known mismatches. Common pattern: "[Brand] AI" → "[Legal Name], Inc." (e.g., Together AI → "Together Computer, Inc.", Character.ai → "Character Technologies, Inc.", Runway ML → "Runway AI, Inc.").
2. Verify the company exists in S&P. If you skipped Rule 0, call get_info_from_identifiers(identifiers=["Company"]) now — if this also returns empty, the company may be too early-stage or not yet indexed.

Rule 2: Subsidiaries have no funding rounds

Companies that are divisions or wholly-owned subsidiaries of larger companies (e.g., DeepMind under Alphabet, GitHub under Microsoft, BeReal under Voodoo) will return zero funding rounds. Their capital events are tracked at the parent level.

How to detect: The status field from get_info_from_identifiers will show "Operating Subsidiary". The references/sector-seeds.md file also flags known subsidiaries with ⚠️ warnings. Skip these for funding queries.

Rule 3: Use get_rounds_of_funding_from_identifiers as the primary tool, not get_funding_summary_from_identifiers

The summary tool is faster but less reliable — it can return errors or incomplete data even when detailed rounds exist. Always use the detailed rounds tool as the primary data source. The summary tool is acceptable only for quick aggregate checks (total raised, round count) and should be verified against the rounds tool if results seem low.

Rule 4: Batch carefully and validate

When processing large company universes (50+ companies), batch in groups of 15–20. After each batch, check for companies that returned empty results and run them through the fallback steps in Rule 1 before moving on.

Rule 5: The role parameter is critical

• company_raising_funds → "What rounds did X raise?" (company perspective)
• company_investing_in_round_of_funding → "What did investor Y invest in?" (investor perspective)

Using the wrong role returns empty results silently. For deal flow digests, you almost always want company_raising_funds. Only use the investor role when specifically analyzing an investor's portfolio activity.

Rule 6: Identifier resolution is case-insensitive but spelling-sensitive

S&P Global handles case variations ("openai" = "OpenAI") but is strict on spelling and punctuation. "Character AI" may fail where "Character.ai" succeeds. When in doubt, use the company_id (e.g., C_1829047235) which is guaranteed to resolve.

Workflow

Step 1: Establish Coverage & Period

Determine what the digest should cover. There are two setups:

Returning user (has a watchlist): If the user has previously defined sectors or companies to track, use that list. Check conversation history for prior watchlists.

New user: Ask for:

Calculate the exact start_date and end_date from the time period.

Step 2: Build the Company Universe

For each sector specified, build a company universe using a validated bootstrapping approach:

1. Seed companies from domain knowledge (see references/sector-seeds.md)

   • Pay attention to the ⚠️ warnings and alias notes in the seeds file — some well-known companies are subsidiaries, have been acquired, or require a specific legal name to resolve.
   • The seeds file includes company_id values for known alias mismatches. Use these directly if the brand name fails.

2. Pre-validate all seeds immediately (Rule 0):

   get_info_from_identifiers(identifiers=[all_seeds_for_this_sector])

   Triage the results into two buckets:

   • ✅ Resolved & Operating (status = "Operating") → proceed to competitor expansion
   • ❌ Unresolved or Subsidiary → retry with alias/legal name from seeds file; subsidiaries are noted for context but excluded from funding queries

3. Expand via competitors (using only the ✅ resolved seeds):

   get_competitors_from_identifiers(identifiers=[resolved_seeds], competitor_source="all")

4. Validate expanded universe:

   get_info_from_identifiers(identifiers=[new_competitors])

   Apply the same triage. Filter by simple_industry matching the target sector. Drop any unresolved names or subsidiaries.

If the user provides specific companies, add those directly but still run them through the pre-validation triage. Never skip validation — even well-known brand names can fail silently.

Keep the universe manageable — aim for 15–40 resolved, operating companies per sector. For a multi-sector digest, this might total 50–100+ companies.

Step 3: Pull Funding Rounds

For all companies in the universe:

get_rounds_of_funding_from_identifiers(
    identifiers=[batch],
    role="company_raising_funds",
    start_date="YYYY-MM-DD",
    end_date="YYYY-MM-DD"
)

Process in batches of 15–20 if the universe is large.

After each batch, identify companies with empty results. For any company expected to have activity:

1. Retry with the legal entity name or alternate identifier (see Entity Resolution rules above).
2. Log the company as "no data" only after exhausting fallbacks.

Collect all transaction_id values from successful results, then enrich with detailed round info:

get_rounds_of_funding_info_from_transaction_ids(
    transaction_ids=[all_funding_ids]
)

Pass ALL transaction IDs in a single call (or small number of calls) rather than one per transaction — the tool handles batches efficiently.

Extract the following from each round (critical for the slide):

• transaction_id — needed for the Capital IQ deal link
• Announcement date — when the round was publicly announced
• Close date — when the round officially closed
• Amount raised
• Pre-money valuation (if disclosed)
• Post-money valuation (if disclosed)
• Lead investors
• Round type (Series A, B, C, etc.)
• Security terms
• Advisors
• Pricing trend (up-round / down-round / flat)

Dates are required. The announcement and close dates must always appear in the final slide's deal table. If only one date is available, show it and mark the other as "—".

Step 4: Pull Company Context for Notable Deals

For any company involved in a significant deal (large round, notable valuation shift), get a brief description:

get_company_summary_from_identifiers(identifiers=[notable_companies])

This adds context to the narrative (e.g., "The company, an AI infrastructure startup founded in 2021, is expanding into...").

Step 5: Identify Highlights & Trends

Before designing the slide, analyze the data to surface the story:

Flag as "Notable":

• Rounds ≥ $100M
• Down rounds (pricing trend = down)
• New unicorns (post-money valuation crossing $1B)
• Significant valuation jumps (post-money ≥ 2x the last known valuation)
• Repeat raisers (same company raising again within 6 months)
• Unusually large investor syndicates

Identify Trends:

• Total capital deployed this period vs. typical (if historical data available)
• Which sub-sectors are hottest (most rounds, most capital)
• Round stage distribution (is early-stage or late-stage dominating?)
• Most active investors across the digest
• Geographic concentration
• Valuation trends (are pre-money valuations compressing or expanding?)

Select Key Takeaways (3–5): Distill the most important signals into 3–5 concise bullet-style takeaways. These are the centerpiece of the slide. Each takeaway should be one sentence, punchy, and data-backed.

Examples:

• "AI sector raised $2.4B across 8 rounds — 3x the prior week, led by a $800M mega-round from [Company] at a $12B post-money valuation."
• "[Company] closed a $200M Series D at $3.5B pre-money, up from $1.8B in its Series C — signaling strong demand for AI developer tools."
• "Down-round activity ticked up: 2 of 6 late-stage rounds priced below prior valuations."

Step 6: Generate Company Logos

For each company featured in the key takeaways or notable deals, generate a logo using a two-tier local pipeline. Do not use Clearbit (logo.clearbit.com) — it is deprecated and consistently fails. External logo CDNs (Brandfetch, logo.dev, Google Favicons) require API keys or are blocked by network restrictions. Instead, use the following approach:

Tier 1: simple-icons npm Package (3,300+ Brand SVGs, No Network Required)

The simple-icons package bundles high-quality SVG icons for thousands of well-known brands. It works entirely offline — no API keys, no network calls. Install it alongside sharp for SVG → PNG conversion:

npm install simple-icons sharp

Lookup strategy:

const si = require('simple-icons');
const sharp = require('sharp');

// Find an icon by exact title match (case-insensitive)
function findSimpleIcon(companyName) {
    // Try exact match first
    for (const [key, val] of Object.entries(si)) {
        if (!key.startsWith('si') || !val || !val.title) continue;
        if (val.title.toLowerCase() === companyName.toLowerCase()) return val;
    }
    // Try without common suffixes (AI, Inc., Corp.)
    const stripped = companyName.replace(/\s*(AI|Inc\.?|Corp\.?|Ltd\.?)$/i, '').trim();
    if (stripped !== companyName) {
        for (const [key, val] of Object.entries(si)) {
            if (!key.startsWith('si') || !val || !val.title) continue;
            if (val.title.toLowerCase() === stripped.toLowerCase()) return val;
        }
    }
    return null;
}

// Convert SVG to PNG with the brand's official color
async function simpleIconToPng(icon, outputPath) {
    const coloredSvg = icon.svg.replace('<svg', `<svg fill="#${icon.hex}"`);
    await sharp(Buffer.from(coloredSvg))
        .resize(128, 128, { fit: 'contain', background: { r: 255, g: 255, b: 255, alpha: 0 } })
        .png()
        .toFile(outputPath);
}

Coverage: ~43% of typical deal flow companies (strong for major tech brands like Stripe, Anthropic, Databricks, Snowflake, Discord, Shopify, SpaceX, Mistral AI, Hugging Face; weaker for niche fintech, biotech, or early-stage companies).

Tier 2: Initial-Based Fallback via sharp (100% Coverage)

For companies not found in simple-icons, generate a clean initial-based logo as a PNG:

async function generateInitialLogo(companyName, outputPath) {
    const initial = companyName.charAt(0).toUpperCase();
    const svg = `
    <svg width="128" height="128" xmlns="http://www.w3.org/2000/svg">
        <circle cx="64" cy="64" r="64" fill="#BDBDBD"/>
        <text x="64" y="64" font-family="Arial, Helvetica, sans-serif"
              font-size="56" font-weight="bold" fill="#FFFFFF"
              text-anchor="middle" dominant-baseline="central">${initial}</text>
    </svg>`;
    await sharp(Buffer.from(svg)).png().toFile(outputPath);
}

Complete Pipeline

async function fetchLogo(companyName, outputDir) {
    const fileName = companyName.toLowerCase().replace(/[\s.]+/g, '-') + '.png';
    const outPath = path.join(outputDir, fileName);

    // Tier 1: Try simple-icons
    const icon = findSimpleIcon(companyName);
    if (icon) {
        await simpleIconToPng(icon, outPath);
        return { path: outPath, source: 'simple-icons' };
    }

    // Tier 2: Generate initial-based fallback
    await generateInitialLogo(companyName, outPath);
    return { path: outPath, source: 'initial-fallback' };
}

Logo guidelines:

• Save all logos to /home/claude/logos/[company-name].png
• All logos are 128×128 PNG with transparent backgrounds
• On the slide, display logos at 0.35"–0.5" tall — they're accents, not focal points
• Initial-fallback circles use gray (BDBDBD) fill with white text — consistent with the monochrome palette
• Never mix logo styles randomly — if most companies resolve to brand icons, the few fallbacks should blend in naturally

Step 7: Generate the One-Page PPTX

Read /mnt/skills/public/pptx/SKILL.md and /mnt/skills/public/pptx/pptxgenjs.md before creating the slide.

Create a single-slide PowerPoint using pptxgenjs. The slide should be information-dense but visually clean — think "executive dashboard" not "wall of text."

Slide Layout

┌─────────────────────────────────────────────────────────────┐
│  DEAL FLOW DIGEST                                           │
│  [Period] · [Sectors]                           [Date]      │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ┌─────────┐  ┌─────────┐  ┌─────────┐  ┌─────────┐       │
│  │  $X.XB  │  │  N      │  │  $X.XB  │  │  $X.XB  │       │
│  │ Raised  │  │ Rounds  │  │ Avg Pre │  │ Largest │       │
│  └─────────┘  └─────────┘  └─────────┘  └─────────┘       │
│                                                             │
│  KEY TAKEAWAYS                                              │
│  ─────────────────────────────────────────────────          │
│  [Logo] Takeaway 1 text goes here...                        │
│  [Logo] Takeaway 2 text goes here...                        │
│  [Logo] Takeaway 3 text goes here...                        │
│  [Logo] Takeaway 4 text goes here...                        │
│                                                             │
│  TOP DEALS                                                  │
│  ┌──────────────────────────────────────────────────────────┐│
│  │Company│Type │Announced│Closed│Amount│Pre-$│Post-$│Lead│🔗││
│  │───────│─────│─────────│──────│──────│─────│──────│────│──││
│  │ ...   │ ... │  ...    │ ...  │ ...  │ ... │ ...  │... │🔗││
│  └──────────────────────────────────────────────────────────┘│
│                                                             │
│  [Footer: Deal Flow Digest · Sources: S&P Global Capital IQ]│
│  [Footer: AI Disclaimer]                                    │
└─────────────────────────────────────────────────────────────┘