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Run2 13f fund summary

Skill cxcscmu/SkillLearnBench/skills/b2-self-feedback-gemini-3.1-pro-preview/financial-analysis/run2_13f-fund-summary

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Install
npx -y skills add cxcscmu/SkillLearnBench --skill run2_13f-fund-summary

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How to calculate a fund's actual AUM and total unique stock count for modern SEC 13F data.

SKILL.md

1.4 KB, as published. Nobody here has run it

Overview

Starting in 2023, the SEC began requiring funds to report exact dollar amounts in the SUMMARYPAGE.tsv and INFOTABLE.tsv VALUE columns, replacing the old system where values were reported in thousands.

Usage Patterns

Calculating True AUM

The total value is now precisely reported in exact dollars.

import pandas as pd

accession_number = "0001037389-25-000064"
quarter = "2025-q3"

summary = pd.read_csv(f"/root/{quarter}/SUMMARYPAGE.tsv", sep="\t", dtype=str)
match = summary[summary["ACCESSION_NUMBER"] == accession_number]

if not match.empty:
    # 13F forms currently report VALUES in EXACT dollars (no longer in thousands)
    aum = float(match["TABLEVALUETOTAL"].iloc[0])
    print(f"Total AUM: ${aum:,.2f}")

Counting Unique Stock Holdings

Since one CUSIP can have multiple rows (for different investment discretion types or voting authority), use nunique() on the CUSIP column.

import pandas as pd

infotable = pd.read_csv(f"/root/2025-q3/INFOTABLE.tsv", sep="\t", dtype=str)
holdings = infotable[infotable["ACCESSION_NUMBER"] == "0001037389-25-000064"]

# Number of unique CUSIPs represents the total number of stocks held
unique_stocks = holdings["CUSIP"].nunique()
print(f"Number of Unique Stocks Held: {unique_stocks}")

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.