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ayeyouok

a207-router-mcp

by ayeyouok

extract_slots

Extracts structured slots from text, identifying patient ID, food, analyte, date, number, measuring unit, and time window. Converts unstructured input into usable data fields.

Instructions

规则抽槽位:patient_id / food / analyte / date / number / 量具 / 时间窗。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full responsibility for disclosing behavior. It mentions 'rule-based' but does not describe whether it modifies input, what the output structure is, error handling, or side effects. The presence of an output schema mitigates this somewhat, but the description itself is insufficient.

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 appropriately short and front-loaded with the core purpose. It is a single, direct sentence without filler, though it could benefit from a brief note on input. It is concise but not minimal to the point of under-specification.

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

Completeness3/5

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

This is a simple tool with a single parameter and an output schema, so it does not require extensive description. However, the lack of usage or behavioral context makes it incomplete for an agent encountering it for the first time. Given the sibling tools, some integration guidance would help but is not critical.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It lists slot types (which are likely output fields) but gives no explanation of the 'text' parameter's meaning or format. The description does not help an agent understand what value to pass, only what the tool extracts.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: rule-based slot extraction, listing specific slot types (patient_id, food, etc.). This is a specific verb+resource that distinguishes it from siblings like check_permission or classify_intent. However, it does not explicitly mention that the input is text, which the schema reveals.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, or any context for its invocation. The description is purely functional without usage scenarios, prerequisites, or exclusions.

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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