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Run2 13f stock search

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

How to find top fund managers heavily invested in a particular stock across all data quality issues.From its SKILL.md

Install
npx -y skills add cxcscmu/SkillLearnBench --skill run2_13f-stock-search

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.4 KB, 351 tokens by cl100k_base, as published. Nobody here has run it

Overview

When searching for funds heavily invested in a single stock, be aware that CUSIP codes might be entered in varying cases (e.g. 69608A108 vs 69608a108), so normalizations like .str.upper() are critical.

Usage Patterns

Finding Top Funds by Value

This strategy avoids issues with case sensitivity and missing commas when parsing TITLEOFCLASS.

import pandas as pd

cusip = "69608A108"
quarter = "2025-q3"

infotable = pd.read_csv(f"/root/{quarter}/INFOTABLE.tsv", sep="\t", dtype=str)
coverpage = pd.read_csv(f"/root/{quarter}/COVERPAGE.tsv", sep="\t", dtype=str)

# Filter by CUSIP defensively
infotable["CUSIP_UPPER"] = infotable["CUSIP"].str.upper()
stock_holders = infotable[infotable["CUSIP_UPPER"] == cusip].copy()

# Sum the VALUE by ACCESSION_NUMBER
stock_holders["VALUE"] = stock_holders["VALUE"].astype(float)
fund_sums = stock_holders.groupby("ACCESSION_NUMBER")["VALUE"].sum().reset_index()

# Sort to get top 3
top_funds = fund_sums.sort_values(by="VALUE", ascending=False).head(3)

# Merge back to COVERPAGE to obtain FILINGMANAGER_NAME
merged = pd.merge(top_funds, coverpage[["ACCESSION_NUMBER", "FILINGMANAGER_NAME"]], on="ACCESSION_NUMBER", how="left")

print(merged[["FILINGMANAGER_NAME", "VALUE"]])

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. 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.