# Investment Portfolio Snapshot > Generate a professional wealth-advisor HTML report showing a current snapshot of someone's investment portfolio, aggregated from raw brokerage CSV exports (any brokerage). Extracts holdings, classifies them by asset type and sector via yfinance, and produces a self-contained HTML report with an AI-written assessment and allocation charts. Use when the user wants a portfolio snapshot, allocation report, or wealth summary from their brokerage export files. - Skill: `adityatandel/investment-portfolio-snapshot` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add adityatandel/investment-portfolio-snapshot` - Raw SKILL.md: https://api.skillmd.com/api/skills/adityatandel/investment-portfolio-snapshot/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Web & Frontend - Author: adityatandel (https://skillmd.com/u/adityatandel) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/adityatandel/investment-portfolio-snapshot --- # Investment Portfolio Snapshot Turns a folder of raw brokerage CSV exports into a professional HTML portfolio report with an advisor-style written assessment and modern allocation charts. Works on Mac, Windows, and Linux. ## Step 0 — Check dependencies FIRST (before anything else) This skill needs: - Python packages `yfinance` and `matplotlib` - A free Alpha Vantage API key (for ETF sector look-through) The report is generated as a single self-contained HTML file (charts embedded as base64 images) — no PDF converter or other external tool is required. Run this check: ``` python3 -c "import yfinance" 2>/dev/null && echo "yfinance OK" || echo "yfinance MISSING" python3 -c "import matplotlib" 2>/dev/null && echo "matplotlib OK" || echo "matplotlib MISSING" [ -n "$ALPHAVANTAGE_API_KEY" ] && echo "ALPHAVANTAGE_API_KEY OK" || echo "ALPHAVANTAGE_API_KEY MISSING" ``` For anything reported MISSING, tell the user what's missing and ask permission to install/set it. Only proceed after they agree: - `yfinance` or `matplotlib` missing: ``` pip install yfinance matplotlib ``` On Windows, if `pip` is not recognized, try `pip3` instead (or vice versa) — which one works depends on how Python was installed. Same applies to every `python3 ...` command in this skill: on Windows, try `python` if `python3` isn't recognized. - `ALPHAVANTAGE_API_KEY` missing: Tell the user this key is a FALLBACK for ETF sector look-through. The skill always tries yfinance first for every symbol (no key needed); Alpha Vantage is only called for an ETF when yfinance has no sector data for it. This keeps Alpha Vantage usage low and conserves its free-tier daily limit. It is free: 1. Sign up at https://www.alphavantage.co/support/#api-key (no credit card) 2. Easiest option: save a plain-text file named `alphavantage_key.txt` in this folder, containing only the key (no quotes, no extra text). The skill checks for this file automatically every run — no re-entry needed. **On a Mac, TextEdit saves Rich Text (.rtf) by default even if you name the file `.txt`.** Tell the user to either use a plain-text editor, or in TextEdit go to Format > Make Plain Text before saving. The skill detects and warns about an RTF file rather than silently failing. 3. Alternative: `export ALPHAVANTAGE_API_KEY=their_key_here` in Terminal (session-only unless added to their shell profile). The env var takes priority over the key file if both are set. If the user prefers to skip this entirely, that's fine — the skill still runs; ETFs will show as "Unclassified" in the sector chart instead of being broken down. The skill checks for the key in this order: environment variable, then `alphavantage_key.txt` / `.alphavantage_key` / `av_key.txt` in the working folder. Do not proceed to Step 1 until dependencies are OK. The API key is optional but strongly recommended — proceed without it only if the user declines. ## Step 1 — Extract & combine holdings ``` python3 ${CLAUDE_SKILL_DIR}/scripts/extract_holdings.py ``` Reads every CSV export in the folder, finds the symbol and market-value columns in each, and writes `holdings_combined.csv` (summing duplicates across files, so the same symbol held at two brokerages adds up correctly into one total). This step also scans each file and reports, by filename: - **Errors** (file excluded from the report): empty files, unreadable/wrong-format files, or files where no Symbol + Market Value column pair could be found. - **Warnings** (file still processed, but flag to the user): a likely account number or similar identifier detected in the file, or transaction rows (trades, dividends, debits/credits, transfers) that were ignored because this report only shows current holdings, not activity history. **Always relay every warning and error to the user by filename, in plain language**, even if the run otherwise succeeds. For an account-number warning, explicitly tell the user which file it's in and ask them to remove that column before their next run — do not proceed to guess or redact it yourself. For a file-level error, tell the user clearly that file's holdings were NOT included and why, so they can fix and re-run if needed. ## Step 2 — Enrich with asset type & sector ``` python3 ${CLAUDE_SKILL_DIR}/scripts/enrich_holdings.py ``` Classifies each holding via yfinance and writes `holdings_enriched.csv`. Results are cached in `classification_cache.csv`; the user may hand-edit that file to correct any misclassification, then re-run this step. If many holdings come back as "Others", mention that they can correct the cache and re-run. ## Step 3 — Write the advisor assessment Read `holdings_enriched.csv` yourself and write a portfolio description of about 2–3 short paragraphs, in the voice of a professional wealth advisor. It must: - Describe the current state first: the equity/bond/cash mix, the risk level it implies, and any notable concentration (sector, single holding, cash). - Then give a LIGHT opinion — what stands out, framed as an observation, not a directive. - Stay measured and professional. Do not invent data not in the file. Save this to `assessment.txt` (plain text, blank line between paragraphs). ## Step 4 — Build the HTML report Ask the user what title/name they want (their name, or e.g. "My Portfolio"). If `portfolio_snapshot.html` already exists in the folder from a previous run, overwrite it directly — do not ask the user whether to proceed. ``` python3 ${CLAUDE_SKILL_DIR}/scripts/build_report.py --description-file assessment.txt --name "PORTFOLIO NAME" ``` Produces `portfolio_snapshot.html` — a single self-contained file (charts are embedded, no external files needed) that opens directly in any browser. It has: - Title, date, total value, holding count - The assessment you wrote (plus a "not financial advice" disclaimer) - Two modern charts: By Asset Type (donut, all holdings) and By Sector (bars, individual stocks only, with coverage %) ## Step 5 — Done Tell the user the report is ready at `portfolio_snapshot.html` — they can open it directly in any browser. ## Rules - Always run Step 0 first; never skip the dependency check. - **Always overwrite existing output files without asking.** This skill is meant to be re-run repeatedly on the same folder. `holdings_combined.csv`, `holdings_enriched.csv`, `assessment.txt`, and `portfolio_snapshot.html` are all expected to be regenerated fresh every run. If any of these already exist from a prior run, overwrite them directly — do not ask the user for confirmation or treat this as a conflict. The one exception is `classification_cache.csv`, which persists intentionally across runs (do not delete it; the scripts update it in place). - The report always prints a clear "not financial advice / guide only" note. - Classification is best-effort. Offer the cache-edit + re-run path if needed. - Never invent market values or holdings. Use only what the files contain. - This skill assumes all values are in USD and does not convert currencies. If the user's files contain non-USD values, warn them that totals and the report's "$" labeling will be inaccurate. - Do not modify the user's raw export files.