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get_mf_overlap

Analyzes mutual fund overlap using public AMFI data to reveal common stocks, uniqueness, and risk level, helping you avoid duplicate holdings and achieve true diversification.

Instructions

Mutual fund overlap analyzer using public AMFI portfolio disclosures.

"Your HDFC Flexi Cap + Mirae Asset Large Cap have 68% overlap — you're not diversified, you're holding the same stocks twice."

Supported funds include: HDFC Flexi Cap, Mirae Asset Large Cap, Parag Parikh Flexi Cap, Axis Bluechip, SBI Bluechip, Nippon Large Cap, Kotak Emerging Equity, Quant Small Cap, DSP Small Cap, Nifty 50 Index.

Returns:

  • overlap_pct: % of stocks common between both funds

  • common_stocks: list of shared holdings

  • unique_to_fund1, unique_to_fund2

  • verdict + risk level (low / medium / high)

Args: fund1: Fund name (e.g. "HDFC Flexi Cap") fund2: Fund name (e.g. "Mirae Asset Large Cap")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fund1Yes
fund2Yes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It transparently states the data source (public AMFI disclosures), lists supported funds, and describes the output fields. However, it does not disclose potential delays, data freshness, or any limitations (e.g., only Indian funds). Overall, it provides solid behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with purpose. It includes a useful example and clearly structured argument information. It could be slightly more concise, but overall it is effective and well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is an output schema, the description appropriately details return values (overlap_pct, common_stocks, etc.) without redundancy. It covers the main functionality but could mention error handling or unsupported fund cases. Overall, it is sufficiently complete for an analysis tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only defines two string parameters with no descriptions (0% coverage). The description compensates fully by providing concrete examples (e.g., 'HDFC Flexi Cap') and listing supported fund names, which is critical for correct invocation. This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a 'Mutual fund overlap analyzer' using public AMFI disclosures, with a specific verb ('analyzes') and resource ('overlap between mutual funds'). It lists supported funds and what it returns, distinguishing it from sibling tools like portfolio_analysis or mutual_fund_nav.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an example of when to use the tool (checking diversification with an overlap example), but does not explicitly contrast it with alternative tools or state when not to use it. The usage context is implied but lacks explicit guidance on selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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