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Fca Largest Shorts

fca_largest_shorts
Read-onlyIdempotent

The N issuers with the largest currently FCA-disclosed net short positions market-wide, sorted descending by aggregated position %. Reads the same daily "aggregated-current-net-short-positions" file as fca_short_positions -- aggregated per issuer, no holder names. Example: fca_largest_shorts({ top_n: 10 }).

Input Schema

NameRequiredDescriptionDefault
top_nNoHow many issuers to return, most-shorted first. Default 20, max 100.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotent/openWorld/non-destructive, so the safety profile is covered. The description adds real behavioral context on top: descending sort order by aggregated position %, per-issuer aggregation, and the absence of holder names. It does not mention pagination or rate limits, keeping it below a 5.

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-loaded with the resource definition, then the data-source note, then an example. Every element is relevant, though the inline example call largely duplicates the schema's own examples block, which is the only minor waste.

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 single-parameter ranking tool with no output schema, the description covers what is returned (top N issuers by aggregated short %), the ordering, the granularity, and the data provenance. Return shape details remain implicit, but nothing essential for correct invocation is missing.

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 description coverage is 100% and the top_n parameter already documents the default (20) and max (100). The description's only parameter-related addition is an inline example call, which does not add syntax or semantic meaning beyond the schema. Baseline 3 applies 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.

Purpose5/5

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

Specific verb+resource: it returns the top-N issuers by aggregated FCA-disclosed net short position, sorted descending by position %. It explicitly distinguishes itself from the sibling fca_short_positions by noting it reads the same daily file but aggregates per issuer with no holder names.

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

Usage Guidelines4/5

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

It clearly signals the use case (ranking the most-shorted issuers market-wide) and positions itself against fca_short_positions, an agent can infer the alternative. It stops short of an explicit 'use X when / use this when not' routing rule, so it is not a 5.

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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