Skip to main content
Glama

derivation_get_saved

Retrieve saved derivation results by ID, including formula, steps, source, clinical significance, limitations, and references.

Instructions

    取得已存檔的推導結果詳情

    Args:
        result_id: 推導結果 ID

    Returns:
        完整的推導結果,包含:
        - 公式表達式
        - 推導步驟
        - 來源公式
        - 臨床/物理意義
        - 使用限制
        - 參考文獻

    Example:
        derivation_get_saved("temp_corrected_elimination")
        → {"success": True, "name": "...", "expression": "...", ...}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
result_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description must carry full burden. It describes the return structure in detail (formula expression, derivation steps, etc.) and provides an example of a success response. However, it does not mention error handling or behavior when the result_id does not exist, which is a gap.

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 structured with Args, Returns, and Example sections. It is front-loaded with the main purpose and uses bullet points for return fields. The example is helpful, but the description is slightly longer than necessary, with some repetition of fields already implied by the tool name.

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?

This is a simple get-by-ID tool with an output schema. The description explains the return fields and provides an example, which covers most of the needed context. It lacks guidance on usage context and edge cases, but for a retrieval tool, it is reasonably complete.

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?

The input schema has 0% description coverage, so the description must compensate. It provides a one-line explanation of result_id as '推導結果 ID' (derivation result ID) and the example shows a string. This adds minimal meaning beyond the parameter name itself.

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 starts with the verb '取得' (retrieve) and the resource '已存檔的推導結果詳情' (saved derivation result details). It explicitly lists the contents of the result, distinguishing it from sibling tools like derivation_list_saved or derivation_search_saved that list or search saved derivations.

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?

No explicit guidance is given on when to use this tool versus alternatives. The example and parameter imply usage when you have a specific result_id and need full details. Sibling tools like derivation_list_saved and derivation_search_saved serve alternative purposes, but the description doesn't mention them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/u9401066/nsforge-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server