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Query and analyze SEC filings and financial statements using EdgarTools. Get company data, filings, XBRL financials, and perform multi-company analysis.
Passed 21 of 22 test cases with the skill, and 9 of 22 without it.
and 14 more in the full report
12 fixed9 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am building an LLM agent that processes SEC company profiles using EdgarTools. Printing the raw Company('AAPL') object consumes over 200 tokens. What method on the Company object should be called to get a concise summary using under 100 tokens? Write a Python snippet showing this.
| Checked | Without skill | With skill |
|---|---|---|
| The Python snippet calls company.to_context() to generate a concise summary. | Missed | Passed |
The instructions your model reads when the skill loads.
Analyze SEC filings and financial statements using EdgarTools
Essential SEC filing analysis operations. See objects.md for object reference, workflows.md for patterns, readme.md for setup.
REQUIRED: Set your identity (SEC requirement):
from edgar import set_identity
set_identity("Your Name [email protected]")
Without this, all API calls fail with "User-Agent identity is not set" error.
ALWAYS use .to_context() first for concise summaries with available actions. 5-10x more token-efficient than full objects.
from edgar import Company
company = Company("AAPL")
print(company.to_context()) # ~88 tokens vs 200+ for full object
Output:
**Company:** Apple Inc.
**CIK:** 0000320193
**Ticker:** AAPL
**Exchange:** Nasdaq
**Industry:** Electronic Computers (SIC 3571)
**Fiscal Year End:** Sep 30
test cases passed, vs 9 / 22 without
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