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Rust
Hybrid

Short Positions

short_positions
Read-onlyIdempotent

Retrieve short interest history for US or HK stocks by passing a symbol with market suffix. Optionally set count (1-100) to get open short positions, ratio, close, and market-specific metrics.

Instructions

Get short interest history (open short positions) for HK or US stocks. Market inferred from symbol suffix. count: 1–100 (default 20). Unified data[]{timestamp(RFC3339), short_shares(open short position in shares), rate(decimal ratio e.g. 0.009=0.9%), close}. US-only: avg_daily_vol, days_to_cover. HK-only: balance(outstanding short position in HKD). US source: FINRA bi-weekly. HK source: HKEX daily.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_jqNoOptional jq filter (jaq syntax) applied to this tool's JSON response before it is returned; it never changes the upstream request. One output is returned as-is, several as a JSON array, none as []. Module imports and the `env`/`debug`/`stderr` builtins are unavailable. Example: .data | map({symbol}). Omit for the full response.
countNoNumber of records to return (1-100, default 20)
symbolYesSecurity symbol, e.g. "AAPL.US" (US) or "700.HK" (HK). Market is inferred from suffix.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.12.0
    • addedInput schema / properties / _jq / description
      Added value: +"Optional jq filter (jaq syntax) applied to this tool's JSON response before it is returned; it never changes the upstream request. One output is returned as-is, several as a JSON array, none as []. Module imports and the `env`/`debug`/`stderr` builtins are unavailable. Example: .data | map({symbol}). Omit for the full response."
    • removedInput schema / properties / count / format
      Removed value: -"uint"
  2. Changed1 schema field changedv0.10.6
    • addedInput schema / properties / _jq
      Added value: +{
+  "type": "string"
+}
  3. Changed1 schema field changedv0.7.1
    • removedInput schema / title
      Removed value: -"ShortPositionsParam"
  4. Addedv0.4.5
  5. Removedv0.4.0
  6. Addedv0.3.2
  7. Removedv0.3.1
  8. First observedv0.1.12

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral context: data source frequency (FINRA bi-weekly, HKEX daily), market inference logic, and field variations by market (US-only vs HK-only). This goes beyond the annotations without contradicting them.

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 front-loaded with purpose and then efficiently packs count, data fields, and sources into a compact paragraph. It avoids fluff and each clause adds information, though the density of field names and sources could be slightly more organized for readability.

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?

With no output schema, the description compensates by enumerating the return fields and market-specific variations, plus data sources. It also clarifies count limits and market inference. Minor gaps like error handling or no-data behavior exist but are not critical for a read-only, idempotent tool with clear input constraints.

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% for all three parameters, each with descriptive text. The description reinforces the count range and suffix inference but adds little new meaning beyond what the schema already provides. The field-level details in the description indirectly clarify the response but not the parameter semantics themselves.

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 states a specific verb ('Get'), a precise resource ('short interest history'), and a clear scope ('HK or US stocks'), distinguishing it from related siblings like short_trades and short_margin by focusing on open positions history. The field list and source details further clarify its exact purpose.

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 clearly indicates when to use the tool (for short interest history) and gives operational details like count range and market inference from suffix. However, it does not explicitly mention alternatives or when not to use it, such as differentiating from short_trades for trading activity or short_margin for margin-based data, leaving some selection ambiguity.

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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