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Claudefarid

dse-stock-mcp

by Claudefarid

Top Movers

top_movers

Identify top gainers, losers, and most traded shares by percentage change during the session. Use direction to filter by gainers, losers, volume, or value.

Instructions

Biggest percentage movers of the session.

direction is 'gainers', 'losers', 'volume' (most shares traded) or 'value' (most taka traded). Ranking uses percent change, not absolute taka, so cheap and expensive shares compare fairly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
directionNogainers

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It usefully discloses that ranking uses percent change rather than absolute taka and defines each direction mode. However, it does not mention ordering behavior, session semantics, or limits, leaving some behavior to be inferred.

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

Conciseness5/5

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

The description is compact and front-loaded, with the core purpose stated first. The ranking rationale is a valuable clarification rather than filler, and every sentence contributes to correct invocation.

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 two-parameter read-only screener, the description covers the critical semantics: valid directions and the ranking methodology. The output schema covers the return shape, and the main remaining gap is the lack of explicit sibling differentiation.

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

Parameters4/5

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

The schema has 0% description coverage and no enums, so the description adds significant meaning by enumerating all valid direction values and clarifying what each represents. The 'limit' parameter is not described in prose, but its name and integer default are sufficiently self-explanatory.

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 'Biggest percentage movers of the session,' which clearly defines the tool's resource and scope. The enumerated direction modes ('gainers', 'losers', 'volume', 'value') make it unmistakable that this is a market-wide screener, distinct from siblings like get_stock or search_stock which target individual tickers.

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

Usage Guidelines2/5

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

No guidance is given about when to prefer this tool over market_summary or the stock-specific siblings. The usage is implied by the name and purpose, but there are no explicit conditions, exclusions, or alternative routing instructions.

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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