Update to Allium

{
  "name": "pdf-reports",
  "description": "**Required for generate_pdf_report tool.**\n\nRead this skill BEFORE calling generate_pdf_report to understand\nhow to write professional analytical reports with narrative depth.",
  "included_files": [],
  "skill_md_contents": "---\nname: pdf-reports\ndescription: |\n  **Required for generate_pdf_report tool.**\n\n  Read this skill BEFORE calling generate_pdf_report to understand\n  how to write professional analytical reports with narrative depth.\n---\n\n# PDF Report Generation\n\n## Report Architecture\n\nEvery report MUST follow this structure. No exceptions.\n\n### 1. Executive Summary (text section)\n\n- 2-3 paragraph narrative. Lead with a thesis statement about the key finding.\n- Bold key statistics inline: **$266.3 billion**, **+317% YoY**.\n- Provide context for every number (vs prior period, vs benchmark, vs market total).\n- NOT a bullet list. Write flowing prose that tells the story.\n\n### 2. Key Insights (text section)\n\n- 3-5 numbered insights. The \"if you read nothing else\" page.\n- Each insight: **Bold headline (10 words max)** followed by supporting data and one-sentence implication.\n- Example: \"**1. Stablecoin payments surpassed credit card volume.** Monthly payment volume hit **$48.3B** in February, exceeding Visa's average merchant settlement volume for the first time. This signals stablecoins are crossing from speculation into real commerce.\"\n\n### 3. Themed Analytical Sections (3-6 sections)\n\nEach theme follows a repeating pattern of three sections:\n\n1. **Context text** (titled) - Why this data matters. Frame the question being answered. 1-2 sentences.\n2. **Chart or table** (titled) - The visualization itself.\n3. **Interpretation text** (empty title `\"\"`) - What the data reveals. Bold the key takeaway. Call out anomalies, benchmarks, or surprising patterns. 2-4 sentences.\n\nThis interleaved pattern is critical. Charts must never appear without surrounding context and interpretation.\n\n### 4. Methodology (text section, for reports with 3+ data sections)\n\n- Data sources and APIs used.\n- Time periods and filters applied.\n- Known limitations or caveats.\n- Keep it brief but honest about what the data does and doesn't cover.\n\n## Content Writing Rules\n\n### Before every chart/table\n\nWrite 1-2 sentences framing what the reader is about to see and why it matters.\n\n### After every chart/table\n\nUse an empty-title text section (`\"title\": \"\"`) for interpretation:\n\n- 2-4 sentences interpreting findings.\n- **Bold the key takeaway** so a skimmer catches it.\n- Call out anomalies, inflection points, or surprising patterns.\n- Provide context: vs prior period, vs benchmark, vs total.\n\n### Statistics and numbers\n\n- Bold key statistics inline: **$266.3 billion**, **+317%**.\n- Always contextualize: \"representing **42%** of total DEX volume, up from 28% last quarter.\"\n- Don't just report WHAT. Explain WHY it matters.\n\n### Section titles\n\n- Use insight-driven titles, not metric-driven titles.\n- Good: \"Payment Adoption Outpaces Speculation\"\n- Bad: \"Daily Trading Volume\"\n\n### Cross-references\n\n- When data in one section relates to another, say so: \"Consistent with the supply shift noted above...\"\n\n## Anti-Patterns (avoid these)\n\n- **Bullet-list executive summaries** - Write prose paragraphs instead.\n- **Naked charts** - Every chart needs context before AND interpretation after.\n- **Data-descriptive section titles** - \"Daily Trading Volume\" tells the reader nothing. Use insight-driven titles.\n- **Reports without methodology** - Include data sources and limitations for any report with 3+ data sections.\n- **Restating numbers without interpretation** - Don't say \"Volume was $10B.\" Say \"Volume hit **$10B**, a **+34%** increase that coincided with the ETH ETF approval.\"\n- **Flat structure** - Don't dump a sequence of charts. Group related data into themed sections with narrative flow.\n\n## Empty-Title Sections\n\nSet `\"title\": \"\"` on a section to render it without a header or TOC entry. The content flows directly below the previous section. Use this for chart/table interpretations:\n\n```json\n{\"title\": \"Payment Adoption Outpaces Speculation\", \"type\": \"text\", \"data\": {\"content\": \"The shift from speculative trading to real payment usage is the defining trend of 2026...\"}},\n{\"title\": \"Monthly Payment Volume\", \"type\": \"chart\", \"data\": {\"chart_type\": \"line\", \"labels\": [\"Jan\", \"Feb\", \"Mar\"], \"values\": [32.1, 48.3, 51.7], \"y_label\": \"Volume ($B)\"}, \"source\": \"Allium API\"},\n{\"title\": \"\", \"type\": \"text\", \"data\": {\"content\": \"Payment volume grew **60%** in Q1, reaching **$51.7B** in March. The acceleration began in February when two major e-commerce platforms integrated USDC checkout. **This is the first quarter where payment volume exceeded speculative trading volume.**\"}}\n```\n\n## Full Example\n\n```json\n{\n  \"title\": \"Stablecoins Infrastructure Report\",\n  \"sections\": [\n    {\n      \"title\": \"Executive Summary\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"The stablecoin market reached a combined market capitalization of **$266.3 billion** in Q1 2026, representing a **+41% increase** year-over-year and surpassing the previous all-time high set in late 2024. This growth was driven primarily by payment adoption rather than speculative trading, marking a structural shift in how stablecoins are used.\\n\\nUSDT maintained its dominant position with **$142B** in circulation, but USDC grew at nearly **3x the rate**, narrowing the gap from 3.2:1 to 2.4:1. The most significant development was the emergence of institutional payment rails, with **$48.3B** in monthly payment volume processed through stablecoin networks in February alone.\\n\\nThis report examines supply dynamics, payment adoption, chain-level infrastructure shifts, and the competitive landscape across the top stablecoin issuers. Data is sourced from Allium's cross-chain analytics covering 15 networks.\"\n      }\n    },\n    {\n      \"title\": \"Key Insights\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"**1. Payment volume surpassed speculative trading for the first time.** Monthly payment volume hit **$48.3B** in February, exceeding trading-related transfer volume. This signals stablecoins are crossing from speculation into real commerce.\\n\\n**2. USDC is closing the gap with USDT at an accelerating rate.** USDC supply grew **+89%** YoY vs USDT's **+31%**, driven by regulatory clarity in the US and EU. The ratio narrowed from 3.2:1 to 2.4:1.\\n\\n**3. Arbitrum and Base captured 62% of new stablecoin deployment.** L2 networks absorbed the majority of new supply, with average transaction costs under **$0.003** making micropayments viable.\\n\\n**4. Institutional on-ramps grew 4x in Q1.** The number of verified institutional wallets holding >$1M in stablecoins increased from 1,200 to 4,800, driven by new custody integrations.\\n\\n**5. Average transfer size dropped 73%, signaling retail adoption.** Median transfer fell from **$4,200** to **$1,150**, consistent with payment use cases rather than treasury management.\"\n      }\n    },\n    {\n      \"title\": \"Supply Growth Signals Structural Demand\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"Total stablecoin supply is the most fundamental indicator of ecosystem health. Unlike trading volume, which can be inflated by wash trading or arbitrage, supply growth reflects genuine demand for dollar-denominated digital assets.\"\n      }\n    },\n    {\n      \"title\": \"Total Stablecoin Supply (Q1 2025 - Q1 2026)\",\n      \"type\": \"chart\",\n      \"data\": {\n        \"chart_type\": \"line\",\n        \"labels\": [\"Q1 2025\", \"Q2 2025\", \"Q3 2025\", \"Q4 2025\", \"Q1 2026\"],\n        \"values\": [188.7, 205.3, 224.1, 248.9, 266.3],\n        \"y_label\": \"Market Cap ($B)\"\n      },\n      \"source\": \"Allium Cross-Chain Analytics\"\n    },\n    {\n      \"title\": \"\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"Supply grew consistently across all four quarters, with **no quarter showing negative growth** for the first time since 2021. **The Q1 2026 figure of $266.3B represents a new all-time high**, surpassing the previous peak of $188B in late 2024. The steady growth pattern, rather than spike-and-crash, suggests structural demand rather than speculative cycles.\"\n      }\n    },\n    {\n      \"title\": \"Payment Adoption Outpaces Speculation\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"The ratio of payment volume to speculative trading volume has been trending upward since mid-2025. This section examines whether the crossover observed in February represents a permanent shift or a temporary anomaly.\"\n      }\n    },\n    {\n      \"title\": \"Monthly Volume by Use Case\",\n      \"type\": \"chart\",\n      \"data\": {\n        \"chart_type\": \"bar\",\n        \"labels\": [\"Oct 2025\", \"Nov 2025\", \"Dec 2025\", \"Jan 2026\", \"Feb 2026\"],\n        \"values\": [38.2, 41.5, 43.8, 45.1, 48.3],\n        \"y_label\": \"Payment Volume ($B)\"\n      },\n      \"source\": \"Allium Payment Classification Model\"\n    },\n    {\n      \"title\": \"\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"Payment volume increased every month in the observation period, reaching **$48.3B in February**. The acceleration in January and February coincided with two major e-commerce platform integrations (Shopify USDC and Stripe stablecoin settlement). **This is the first sustained period where payment volume exceeded speculative transfer volume**, though the classification model carries a ~5% margin of error on the payment/speculation boundary.\"\n      }\n    },\n    {\n      \"title\": \"Chain-Level Infrastructure Shifts\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"Where stablecoins live matters as much as how much exists. Chain selection reflects cost sensitivity, speed requirements, and ecosystem maturity.\"\n      }\n    },\n    {\n      \"title\": \"Stablecoin Supply by Chain\",\n      \"type\": \"chart\",\n      \"data\": {\n        \"chart_type\": \"pie\",\n        \"labels\": [\"Ethereum\", \"Tron\", \"Arbitrum\", \"Base\", \"Solana\", \"Other\"],\n        \"values\": [112.5, 58.2, 38.4, 27.1, 18.9, 11.2]\n      },\n      \"source\": \"Allium Cross-Chain Analytics\"\n    },\n    {\n      \"title\": \"\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"Ethereum remains the largest host at **$112.5B (42%)**, but its share declined from 51% a year ago. **Arbitrum and Base together captured 62% of new supply deployment in Q1**, reflecting the migration to lower-cost L2 infrastructure. Tron's **$58.2B** remains concentrated in emerging market remittance corridors, a use case largely separate from the DeFi ecosystem.\"\n      }\n    },\n    {\n      \"title\": \"Methodology\",\n      \"type\": \"text\",\n      \"data\": {\n        \"content\": \"**Data sources:** Allium cross-chain analytics covering 15 EVM and non-EVM networks. Supply figures include USDT, USDC, DAI, FRAX, and PYUSD with market cap >$100M.\\n\\n**Time period:** Q1 2025 through Q1 2026 (April 1, 2025 - March 31, 2026). Monthly figures use end-of-month snapshots.\\n\\n**Payment classification:** Allium's proprietary model classifies transfers as payment vs speculative based on wallet clustering, counterparty analysis, and transaction patterns. Margin of error: ~5%.\\n\\n**Limitations:** Cross-chain bridge transfers may be double-counted in supply totals. Tron data excludes unverified contract deployments. L2 supply figures include bridged assets from Ethereum.\"\n      }\n    }\n  ],\n  \"options\": {\n    \"subtitle\": \"Q1 2026 Analysis\",\n    \"author\": \"Allium Research\",\n    \"date\": \"March 2026\",\n    \"include_toc\": true\n  }\n}\n```\n\n## Workflow\n\n1. Gather data using `run_sql_query`\n2. Plan your report architecture: identify 3-5 themes from the data\n3. Write the executive summary and key insights FIRST (forces you to identify the story)\n4. Build themed sections with the text > chart > interpretation pattern\n5. Add methodology section\n6. Call `generate_pdf_report` with the structured sections\n\n## Section Types Reference\n\nAll section types support an optional `source` field for data attribution (rendered as small gray text below the content).\n\n### Table\n\n```json\n{\n  \"title\": \"Token Holdings\",\n  \"type\": \"table\",\n  \"data\": {\n    \"columns\": [\"Token\", \"Balance\", \"USD Value\"],\n    \"rows\": [[\"ETH\", \"1.5\", \"$5,000\"], [\"USDC\", \"1,000\", \"$1,000\"]]\n  },\n  \"source\": \"Allium API\"\n}\n```\n\n### Chart\n\n```json\n{\n  \"title\": \"Portfolio Allocation\",\n  \"type\": \"chart\",\n  \"data\": {\n    \"chart_type\": \"pie\",\n    \"labels\": [\"ETH\", \"USDC\"],\n    \"values\": [5000, 1000]\n  },\n  \"source\": \"CoinGecko\"\n}\n```\n\nChart types: `pie` (allocation), `line` (time series), `bar` (comparison)\n\nOptional: `x_label`, `y_label` for line/bar charts.\n\n### Text\n\n```json\n{\n  \"title\": \"Summary\",\n  \"type\": \"text\",\n  \"data\": {\n    \"content\": \"Total portfolio value: $6,000 across 2 tokens. Supports **bold** and *italic* markdown.\"\n  }\n}\n```\n\n## Options\n\n- `orientation`: \"portrait\" (default) or \"landscape\" for wide tables\n- `include_timestamp`: true (default) or false\n- `subtitle`: subtitle displayed on the cover page\n- `author`: author name on cover page\n- `date`: date string on cover page\n- `include_toc`: false (default) or true - adds a table of contents page. Use for reports with 4+ sections.\n"
}