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tanmaymish

MarketPulse MCP

by tanmaymish

get_mf_overlap

Identify overlapping stocks between two mutual funds from AMFI data. Provides overlap percentage, common holdings, unique stocks, and risk verdict to reduce duplicate exposure.

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 the burden. It discloses the data source (public AMFI portfolio disclosures), lists the return fields including 'verdict + risk level', and implies limitations by listing supported funds. It does not detail error handling or data freshness, but the key behavioral aspects are covered.

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 well-structured with sections for supported funds, returns, and args. It is longer than the bare minimum but every part adds value; the motivating quote is slightly extraneous but reinforces purpose. Overall it is efficient and front-loaded with a clear summary.

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?

For a simple 2-parameter tool, the description covers the essential context: data source, supported funds, and detailed return structure. It does not mention edge cases like unsupported fund name formats or portfolio disclosure lag, but given the output schema exists and the tool's simplicity, it is largely complete.

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?

Schema descriptions are absent (coverage 0%), but the description compensates by explaining both fund1 and fund2 with examples ('HDFC Flexi Cap'), and further clarifies by naming the supported fund list. This fully conveys parameter meaning and constraints.

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 opens with 'Mutual fund overlap analyzer using public AMFI portfolio disclosures,' giving a specific verb (analyzer) and resource (mutual fund overlap). This clearly distinguishes it from sibling tools like mutual_fund_nav or amfi_fund_flows by focusing on overlap comparison.

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 example quote illustrates a common use case (assessing diversification between two funds) but does not explicitly state when to use this tool over alternatives. There is no mention of exclusions or when-not-to-use, so usage is implied rather than explicitly guided.

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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