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armaaar

thndr-mcp

by armaaar

Portfolio allocation

get_portfolio_allocation
Read-onlyIdempotent

View how a Thndr portfolio is weighted by market value and grouped by asset class and sector for Egypt, US, UAE, or simulator markets.

Instructions

All markets: holdings weighted by market value and grouped by asset class and by sector ("Unclassified" or "Funds (no sector)" when Thndr gives none). Egypt (and the simulator, through Egypt's data): sectors from the market snapshot and buckets by index membership (EGX30, EGX70 EWI, Shariah…; they overlap and do not sum to 100%). US and UAE: sectors from instrument details (at most 30 holdings, heaviest first) and no index buckets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoMarket: "egypt" (EGX, default), "us" (NYSE/Nasdaq via Alpaca), "uae" (ADX) or "simulator" (paper trading)egypt

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnly=true, idempotent=true, openWorld=true, and non-destructive, so the safety profile is covered. The description adds useful behavioral detail about data provenance and bucket semantics, which is genuinely beyond the annotations. However, it omits the US/UAE truncation trigger ('at most 30 holdings, heaviest first') as a caveat only in passing and says nothing about empty-portfolio behavior or response shape.

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

Conciseness2/5

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

The single dense sentence is packed with parenthetical caveats and overlapping index-membership trivia ('they overlap and do not sum to 100%') that cost reading effort disproportionate to the value delivered. Front-loaded subject is fine, but the mid-clause clutter hurts scannability.

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

Completeness3/5

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

Covers market-specific data sources and bucketing rules, which is meaningful context for a read-only aggregation tool. But with no output schema and no response-shape hint, an agent still cannot predict the return structure well enough to chain results reliably.

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

Parameters3/5

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

Schema coverage is 100% and the single enum parameter is fully documented in the schema. The description implies market-specific output differences but adds no syntax or format detail beyond what the schema's enum description already provides. Baseline 3 is correct when the schema does the heavy lifting.

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+resource (allocation of a portfolio's holdings by asset class and sector) and clearly differentiates its output shape from siblings like get_account_positions or get_portfolio_performance. It is dense but an agent can tell what it returns without opening a schema.

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 implies when the output differs by market (Egypt vs US/UAE/simulator behavior) but never states when to prefer this tool over siblings like get_portfolio_performance or get_account_summary. The market-dependent behavior hints at usage context but no alternatives or exclusions are named.

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