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goransh-gattani

bse-mcp

list_scrips

Fetch BSE securities from the List of Securities page by segment, status, group, name fragment, or exact scrip code, returning paginated rows and total counts.

Instructions

List BSE securities from the List of Securities page, filtered by segment (Equity, EQT0, MF, HS, MB, 'Preference Shares', 'Debentures and Bonds', 'Equity - Institutional Series', 'Commercial Papers', 'Government Securities', 'Certificate of Deposit', 'Treasury Bills'), status (Active/Suspended/Delisted/''), group code (A, B, T, ...), a name fragment, or one exact code. Returns up to limit rows and the total count. Big segments without a name filter are several MB on BSE's side; add a filter when you can.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNo
limitNo
statusNoActive
segmentNoEquity
scripcodeNo
name_containsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose the return shape (up to `limit` rows plus a total count) and a performance/size caveat about BSE's side. It stops short of stating read-only nature, auth requirements, rate limits, or error behavior, so it is strong but not complete.

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?

Front-loads what the tool lists, then filters, then the performance caveat. The long segment enumeration is dense but earns its place given the total absence of enums in the schema, though the single sentence is somewhat overloaded.

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 six-parameter, zero-annotation, no-output-schema tool, the description covers filters, return shape, and the size pitfall. The remaining gap is sibling disambiguation (search_scrips) and any mention of permissions or failure modes, which keeps it from being fully 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 description coverage is 0% and the schema only exposes bare titles plus defaults, so the description has to compensate — and it does, enumerating accepted segment values, status values (Active/Suspended/Delisted/''), group code examples, and mapping scripcode to 'one exact code' versus name_contains to 'a name fragment'. Every one of the six parameters gains meaning the schema does not provide.

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

Purpose4/5

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

States a specific verb (List) and resource (BSE securities from the List of Securities page) plus the filter dimensions. It is precise about what is returned, but never distinguishes itself from the sibling search_scrips, which an agent would reasonably confuse it with.

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?

Gives one real usage condition — add a filter because unfiltered big segments return several MB — which is genuinely actionable. However, it offers no guidance on when to choose this over search_scrips or the other lookup siblings, leaving the main selection decision implicit.

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