القائمة
Parse and analyze SEC 13-F filing TSV datasets to extract AUM, holdings count, and fund details by accession number.
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/cxcscmu/SkillLearnBench --skill sec-13f-analysisيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Handles reading, populating, and saving .docx files using the python-docx library. Use this skill for any tasks involving template filling or modifying Word documents.
Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
This skill includes search capability in 13F, such as fuzzy search a fund information using possibly inaccurate name, or fuzzy search a stock cusip info using its name.
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| name | sec-13f-analysis |
| description | Parse and analyze SEC 13-F filing TSV datasets to extract AUM, holdings count, and fund details by accession number. |
SEC Form 13-F datasets consist of TSV files downloaded from EDGAR. Each quarter has the same file structure.
| File | Purpose |
|---|---|
COVERPAGE.tsv | Fund identity: FILINGMANAGER_NAME, ACCESSION_NUMBER, REPORTCALENDARORQUARTER |
SUMMARYPAGE.tsv | Aggregated stats: TABLEVALUETOTAL (AUM in thousands), TABLEENTRYTOTAL (number of holdings) |
INFOTABLE.tsv | Individual holdings: CUSIP, NAMEOFISSUER, VALUE (thousands), SSHPRNAMT (shares) |
SUBMISSION.tsv | Filer metadata |
import pandas as pd
q3_dir = "/root/2025-q3"
coverpage = pd.read_csv(f"{q3_dir}/COVERPAGE.tsv", sep="\t", dtype=str)
summarypage = pd.read_csv(f"{q3_dir}/SUMMARYPAGE.tsv", sep="\t", dtype=str)
infotable = pd.read_csv(f"{q3_dir}/INFOTABLE.tsv", sep="\t", dtype=str)
row = summarypage[summarypage["ACCESSION_NUMBER"] == accession_number]
aum_thousands = int(row["TABLEVALUETOTAL"].iloc[0])
aum_dollars = aum_thousands * 1000
holdings = infotable[infotable["ACCESSION_NUMBER"] == accession_number]
num_holdings = len(holdings)
# Or use TABLEENTRYTOTAL from SUMMARYPAGE for the reported count
holdings = infotable[infotable["ACCESSION_NUMBER"] == accession_number].copy()
holdings["VALUE"] = pd.to_numeric(holdings["VALUE"], errors="coerce")
holdings["SSHPRNAMT"] = pd.to_numeric(holdings["SSHPRNAMT"], errors="coerce")
VALUE in INFOTABLE is in thousands of USDTABLEVALUETOTAL in SUMMARYPAGE is also in thousands of USDTABLEENTRYTOTAL is the number of positions reported