Trustbase Lab · rCB & Chemical Recycling Data

Grade Price Trend

get_grade_trend

Read-onlyIdempotent

Purpose: return the historical series of the layered rCB index for one grade tier - period-by-period assessedbenchmark price, period-on-period change, anchor, adjustment factor and verification factor. Guidelines: gradedefaults to P2 in the CN region; set start_date and end_date as YYYY-MM to slice a window; pair withget_rcb_index for the current cross-section and get_price_trend for category-level trends. Limits: index pointsonly - dimensionless, non-tradable, and never to be converted into an absolute price; early periods may carry ananchor carried forward from an earlier month, and the output flags when this happens. Ex:get_grade_trend(grade='P2'), get_grade_trend(grade='P1', start_date='2025-12', end_date='2026-09').

Input Schema

TableJSON Schema

Name	Required	Description
`grade`	No	层级，默认 P2
`region`	No	区域，默认 CN
`end_date`	Yes	结束期 YYYY-MM
`start_date`	Yes	起始期 YYYY-MM

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Human-readable result (markdown, or a JSON string when response_format=json).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "text": {
+      "description": "Human-readable result (markdown, or a JSON string when response_format=json).",
+      "type": "string"
+    }
+  },
+  "required": [
+    "text"
+  ],
+  "type": "object"
+}

AddedSep 17, 2026

TDQS

A4.9/5.0

Behavior5/5

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

The description discloses key behavioral traits beyond the annotations: 'index points only - dimensionless, non-tradable, and never to be converted into an absolute price' and 'early periods may carry an anchor carried forward from an earlier month, and the output flags when this happens.' These are non-obvious caveats an agent needs and are not visible in the schema or annotations.

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

Conciseness5/5

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

The description is front-loaded with the purpose, then guidelines, limits, and examples. Every sentence earns its place: purpose, defaults, date format, sibling routing, non-tradability caveat, anchor caveat, and examples are all packed into a compact labeled structure.

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

Completeness5/5

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

Given the output schema exists, the description doesn't need to explain return fields in detail. It covers purpose, usage, limitations, caveats, defaults, and examples. Nothing essential is missing for an agent to select and invoke this tool correctly among 30 siblings.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents all four parameters. The description adds extra semantics by explaining defaults and giving examples such as get_grade_trend(grade='P2') and get_grade_trend(grade='P1', start_date='2025-12', end_date='2026-09'). It could go slightly further by clarifying that start_date and end_date are optional in practice despite being marked required, but the examples imply this.

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 begins with a specific verb-resource pair: 'return the historical series of the layered rCB index for one grade tier' and lists exact output components (assessed benchmark price, period-on-period change, anchor, adjustment factor, verification factor). This clearly differentiates get_grade_trend from siblings like get_rcb_index and get_price_trend by naming them explicitly.

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

Usage Guidelines5/5

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

The Guidelines section states the default grade/region, instructs date formatting as YYYY-MM, and explicitly says 'pair with get_rcb_index for the current cross-section and get_price_trend for category-level trends.' This gives an agent clear when-to-use and when-not-to-use context relative to siblings.

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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