What Data for This Category Looks Like
Iron ore-related data is primarily sourced from commodity spot trading platforms, futures delivery warehouse public disclosure systems, and monthly industry research summaries. Update schedules include multiple rounds of real-time spot data, futures settlement data released after daily market close, and weekly industry supply and demand reports. Document structures fall into two categories: structured reports and unstructured analysis reports. Structured reports include category identifiers, origin classifications, transaction benchmark parameters, and circulation link data fields. Units cover two standard categories: weight measurement and price valuation.
Constraints on Tool Calling and Plugins
Iron ore data’s multi-source nature and differing update schedules impose three core constraints on tool calling and plugin configuration. First, field naming is inconsistent across different data sources. For example, some platforms label iron content as grade, while others use iron element percentage. Unified mapping rules must be configured before tool calling to prevent parameter misalignment. Second, spot data updates more frequently than futures data. Differentiated cache expiration times must be set for different data sources to avoid outdated data being used in marketing content. Third, marketing content must accurately match the iron ore category. A mandatory category filter parameter must be added during tool calling to prevent mixing in data from other steel categories such as coke and steel.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
tool_call_timeout | 300 seconds | Iron ore-related data source interfaces typically respond within 2-3 minutes. Reserve sufficient buffer time to avoid timeout interruptions |
plugin_cache_ttl | 1800–3600 seconds | Spot data updates more frequently than futures data. This interval covers the caching needs of both data source types |
field_mapping_rule | Map according to "origin → origin identifier, price → valuation unit + value" | Field naming varies widely across different data sources. Unified mapping ensures consistency of tool calling parameters |
category_filter_tag | Use "iron ore" as a mandatory matching field | Prevent the tool from returning data from other steel categories, and accurately match the needs of the targeted iron ore category |
qps_limit | Calibrated based on actual platform testing | Different data source interfaces have independent QPS limits. Adjust based on call frequency to avoid triggering rate limits |
response_parse_mode | Structured JSON parsing mode | Most iron ore data is presented as structured reports. Use structured parsing to directly extract target fields for marketing content generation |
Three Common Misconfigurations
- Symptom: The tool frequently returns a 429 Too Many Requests status code. Cause: The
qps_limitconfiguration was not adjusted based on the actual QPS limits of the data source, exceeding the interface call quota. - Symptom: The tool returns results that include unrelated steel category data such as coke and steel. Cause: No
category_filter_tagmandatory filter parameter was configured, causing the tool to match non-target category data. - Symptom: The price value returned by the tool does not match the public data source. Cause: No
field_mapping_rulewas configured, and valuation units of wet ton and dry ton were mixed, leading to incorrect value conversion.
How to Verify Proper Configuration
- A test request containing "iron ore spot price" is submitted. The returned tool data is checked to confirm it only includes iron ore-related content, with no other steel category data.
- More than 10 identical consecutive requests are submitted. All interface return status codes are checked to confirm they are 200, with no frequent rate limit errors.
- The price value returned by the tool is compared with the valuation unit of the public data source, to confirm the value and unit match correctly.
- Tool calling logs are reviewed to confirm the field mapping rule has taken effect, and that target fields have been correctly extracted and populated.
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.