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fuzzy-name-search

Match approximate fund and stock names using rapidfuzz and pandas.

Updated Jan 15, 2026
Search Tags:#pandas#stock#data-processing#fuzzy-search#fund#13f#rapidfuzz
One-click install
npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill fuzzy-name-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fuzzy-name-search
Source: https://github.com/KaiserWhoLearns/skillsbench/tree/main/tasks/sec-financial-report/environment/skills/fuzzy-name-search
Command: npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill fuzzy-name-search

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, rapidfuzz, and includes scripts (resource) components.

What problem does it solve?

Quickly locate fund and stock information when only an approximate name is known, reducing manual search time and misidentification.

Core Features & Use Cases

  • Fuzzy-name search across 13F fund information and issuer data to surface closest matches even with misspellings.
  • Supports both fund-name and stock issuer lookups, returning key identifiers such as accession numbers, quarter, and issuer details.
  • Real-world use: a financial analyst can identify a fund or stock by typing a partial or misspelled name and receiving ranked results with relevant metadata.

Quick Start

Run a fuzzy-name search against funds and stock data using the provided Python scripts.

Frequently Asked Questions about fuzzy-name-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search 13F fund data when I only have a partial or misspelled fund name?▼

Fuzzy-name search allows locating 13F fund data using approximate names by applying rapidfuzz string similarity to match user queries against fund information and return ranked closest matches with relevant metadata.

Can I find stock issuer information using pandas if the exact company name is unknown?▼

Yes, pandas data handling combined with rapidfuzz string similarity enables fuzzy-name search across stock issuer data to surface closest matches even with misspellings, returning key identifiers like issuer details.

What is the best way to map approximate user queries to financial data identifiers?▼

Mapping approximate user queries to financial data identifiers is best achieved through fuzzy-name search, which uses rapidfuzz to calculate string similarity and rank results against 13F fund and stock issuer information.

Does fuzzy-name search return specific metadata like accession numbers for 13F filings?▼

Yes, fuzzy-name search supports both fund-name and stock issuer lookups, returning key identifiers such as accession numbers, quarter, and issuer details alongside the ranked closest matches from the 13F data.

Do I need rapidfuzz and pandas to perform fuzzy-search on financial data?▼

Yes, performing fuzzy-search on financial data requires Python scripts using rapidfuzz for string similarity calculations and pandas for data handling to process the 13F fund and issuer information.

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