The active-group table this service rotates on: product, active ingredient, and IRAC mode-of-action group. Cite the group number when you record a treatment.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_active_groups"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that this table is the reference the service "rotates on," which hints the data is authoritative and static reference data, but says nothing about whether the list is paginated, how often it changes, or what the returned shape looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences with no filler and the resource is front-loaded. The phrasing "the active-group table this service rotates on" is slightly convoluted but does not waste space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter reference lookup with no output schema, the description covers the important ground: what the table contains and how the agent should use the returned value. Missing only return-format and freshness details, which are minor for a static reference list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the baseline there is nothing for the description to compensate for. The description's enumeration of the columns (product, active ingredient, IRAC mode-of-action group) is a small bonus for anticipating the response shape.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the resource (the active-group table) and enumerates its columns, but it never uses a verb — it never says this tool returns or lists that table. An agent can infer it is a reference lookup, yet the statement of what the tool actually does is implicit rather than explicit, and no sibling (check_rotation, get_thresholds) is named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Cite the group number when you record a treatment" gives an implied usage context, which is more than nothing. But there is no statement of when to call this versus check_rotation or get_thresholds, and no exclusions or prerequisites.
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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