Lord1Egypt Edgar Risk Diff
What is new in this company's risk factors vs. last year? This skill answers that question in seconds, for any US-listed ticker, by pulling the two most recent 10-Ks from SEC EDGAR and producing a structured diff of Item 1A (Risk Factors).
When to use this skill
Activate when the user asks any of:
- "What changed in {ticker}'s 10-K risk factors?"
- "What new risks did {ticker} disclose this year?"
- "Did {ticker} drop any risk factors compared to last year?"
- "Compare {ticker}'s risk factors between {year1} and {year2}."
- "Scan {tickers…} for new AI / cyber / China / regulatory risks."
- "Pull the latest risk factors for {ticker}."
Do NOT use this skill for:
- 10-Q diffs (this skill is 10-K only — Item 1A typically only changes annually).
- Live price / earnings / fundamentals (use a market-data skill instead).
- Legal advice. Output is informational only.
Quick start
# Diff the two most recent 10-Ks
python3 {baseDir}/scripts/risk_diff.py diff AAPL
# Diff specific years
python3 {baseDir}/scripts/risk_diff.py diff TSLA --years 2024 2022
# Print the latest Risk Factors section (no diff)
python3 {baseDir}/scripts/risk_diff.py latest NVDA
# One-line summary across many tickers (great for morning briefs)
python3 {baseDir}/scripts/risk_diff.py scan AAPL MSFT GOOGL NVDA META AMZN
# [premium] Embedding-based novelty score — ranks paragraphs by how new they
# actually are, not just whether the text differs.
python3 {baseDir}/scripts/risk_diff.py novelty AAPL --top 10
What the diff output contains
- Churn percentage — fraction of paragraphs that were added, removed, or modified.
- New themes — rollup of added paragraphs by topic (Cybersecurity, AI/ML, Geopolitics, Climate, Supply chain, Regulation, Litigation, Macro, Workforce, Crypto, Pandemic).
- Added paragraphs — risk language that did not exist in the prior 10-K, each tagged with the themes it hits.
- Removed paragraphs — language the company dropped (often as meaningful as what they added).
- Modified paragraphs — old/new pairs with a similarity ratio, so the user can see how a known risk has been re-framed.
Free vs. premium
| Capability | Free | Premium |
|---|---|---|
| Diff (added/removed/modified) | ✅ | ✅ |
| Theme rollup (keyword-based) | ✅ | ✅ |
| Multi-ticker scan | ✅ | ✅ |
| Semantic novelty score (embedding-based, catches paraphrased risks that the keyword diff misses) | ❌ | ✅ |
| Priority email support | ❌ | ✅ |
Premium unlocks the novelty subcommand. Buy a license key at the listing and
save it to ~/.edgar-risk-diff/license.txt, or export
EDGAR_RISK_LICENSE=<key>.
Data source & rate limiting
- Reads from
data.sec.govandwww.sec.gov/Archives/(public, free, no auth). - Throttles to under 10 req/s per SEC fair-access policy.
- Caches all responses in
~/.edgar-risk-diff/cache/— subsequent runs on the same ticker are instant. - Sends an EDGAR-compliant
User-Agentheader. Override withEDGAR_USER_AGENT="Your Name your@email.com"if redistributing.
Security & permissions
No API keys. No credentials. No outbound writes.
- Makes HTTPS GET requests to
data.sec.govandwww.sec.govonly. - Writes only inside
~/.edgar-risk-diff/(cache + optional license file). - No telemetry. No analytics. No third-party calls.
- Review
scripts/risk_diff.py(≈350 lines, single file, pure stdlib + requests) before first use.
Limitations
- Item 1A detection is regex-based and works on standard 10-K formatting. Filings
that use highly non-standard HTML may fail to extract — re-run with
latestto see what the parser sees. - Paragraph matching is fuzzy (SequenceMatcher + hashed-bigram cosine). Very short paragraphs (<40 chars) are ignored to suppress noise.
- Premium novelty uses a deterministic hashed-bigram embedding — runs locally, no external API. Quality is below a transformer model but catches the paraphrase patterns this skill is designed for.