Preface¶

Researchers studying futures delivery typically manage several data tables simultaneously: exchange-registered warehouse warrants, designated delivery warehouse inventories, effective forecasts, industry inventories, open interest in contracts nearing delivery, as well as contract timelines and historical delivery data. These data originate from different metrics—physical tons, number of warrants, and contract lots. Piecing them together directly often leads to meaningless conclusions. One might unify the quantity metrics but forget the contract lot conversion, or convert the lots but fail to align the baselines for the same period.

The Fanwei Fiona Warehouse Warrant, Inventory & Delivery Data Skill is designed to integrate this specific workflow. It inputs the aforementioned data types, unifies the metrics for quantity and contract lots, and outputs warehouse warrant coverage ratios, open interest retention rates, and same-period comparison results. The following section outlines its positioning, capability boundaries, and prerequisites for use.

What This Is¶

This is an Agent Skill designed for futures delivery research, published by Dongzheng Futures. It is located at @finoview/fiona-warehouse-delivery-pressure, with a current version of 1.0.2. It is tagged as “enterprise” source and categorized as “professional” on SkillHub.

It solves the problem of transforming scattered warehouse warrant and delivery data—spanning different sources and units of measurement—into comparable ratio indicators. It also provides same-period comparisons to facilitate the assessment of warrant pressure and open interest retention for contracts approaching delivery.

Core Functions¶

According to the official description, the data inputs used by this Skill include:

1. Registered Warehouse Warrants
2. Designated Delivery Warehouse Inventory
3. Effective Forecasts
4. Industry Inventory
5. Open Interest in Contracts Nearing Delivery
6. Contract Timeline (Expiry)
7. Historical Delivery Data

In terms of metric handling, it performs two simultaneous tasks: first, unifying physical quantity metrics; and second, converting quantities into contract lot metrics. This avoids common errors such as “using ton counts directly as lot counts.”

The output side organizes three items:

1. Warehouse Warrant Coverage: Uses warrant/inventory data to measure the extent to which available physical delivery goods cover the open interest.
2. Open Interest Retention Rate: Measures how much of the open interest in near-delivery contracts is retained through to the actual delivery process within the delivery window.
3. Same-Period Comparison Results: Places current calculation results alongside same-period baselines in a single comparison table for horizontal analysis.

Installation & Activation¶

The crawled materials do not provide installation commands or configuration fields for this Skill, offering only the name, coordinates, version, source, and tags. Therefore, this article does not speculate on the installation method; please refer to the official pages:

Official Address: https://api.skillhub.cn/finoview/fiona-warehouse-delivery-pressure
SkillHub Page: https://www.skillhub.cn/skills/finoview/fiona-warehouse-delivery-pressure

regarding configuration, the tags contain one mandatory piece of information: requires_api_key=true. You must prepare a valid API Key before activation and configure it in the appropriate location for your specific Agent runtime (Cursor, Codex CLI, Claude Code, etc.). Specific field names should follow the instructions on the official page; this article makes no speculations.

Typical Usage¶

The crawled materials do not provide official reproducible examples. Below is an illustration of a typical call structure based on the inputs and outputs declared in the Skill’s description, to help you assess whether you need this capability. For specific parameter formats, please refer to the official page.

A single call typically requires the following inputs:

1. Target contract and near-delivery date, used to define the scope of “contracts nearing delivery.”
2. Quantities of Registered Warehouse Warrants, Designated Delivery Warehouse Inventory, Effective Forecasts, and Industry Inventory.
3. The contract’s Open Interest (in lots).
4. Contract timeline information, and historical delivery data for same-period comparison.

The return result is a unified metric output, not a raw data table:

1. Warehouse Warrant Coverage, provided in both physical quantity and contract lot metrics.
2. Open Interest Retention Rate.
3. Same-period comparison results, used to determine the current value’s position relative to historical averages.

If you only need specific indicators, it is recommended to explicitly specify them during the call to avoid the overhead of returning a full comparison.

Use Cases & Notes¶

Suitable scenarios:

1. Assessing warrant pressure for contracts nearing delivery, where warrants, inventory, forecasts, and open interest must be analyzed together.
2. When physical quantities need to be converted into contract lots before calculating coverage or retention rates.
3. When same-period comparison is required, rather than looking at absolute values from a single point in time.

Points to note:

1. API Key Required. requires_api_key=true means calls will fail without proper credentials. Verify credential availability before troubleshooting other issues.
2. Version Information. The current version is 1.0.2, an early release. Interfaces or fields may change in the future; check the official page’s version history before upgrading.
3. Input Data Quality Determines Output Quality. Registered warrants, delivery warehouse inventory, and industry inventory come from different metrics. Ensure their statistical timestamps and scopes are consistent before input; otherwise, coverage ratios may be skewed by metric discrepancies.
4. Scope of the Skill. This Skill only performs metric unification and indicator calculation; it does not handle data source collection. You must independently acquire the seven types of data mentioned above before submitting them for processing.
5. Reference Material. This article is based on crawled data that did not include installation commands, configuration fields, or official examples. Please refer to the official page for these details.

Conclusion¶

The value of this Skill lies in solidifying the most error-prone part of delivery research—unifying quantity and lot metrics—into a single call. It outputs warehouse warrant coverage, open interest retention, and same-period comparisons. It does not replace data collection, nor does it provide market forecasts; it simply calculates the data you already have using unified metrics.

Official Address: https://api.skillhub.cn/finoview/fiona-warehouse-delivery-pressure
SkillHub Page: https://www.skillhub.cn/skills/finoview/fiona-warehouse-delivery-pressure