lgl_list_groupsConstituent groups (e.g. Board Member, Staff, Volunteer) with their ids and keys. Use the ids and names when recording gifts or filtering searches. LGL: GET /api/v1/groups.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of entries to return, 1-100. LGL's default is 25. | |
| offset | No | Start at this entry (0-based). Use the previous page's next_item. Default 0. |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already tells the agent this is a safe read, so the description needs only to add context. It does add that groups carry ids and keys and cites the underlying GET endpoint, confirming read behavior. It says nothing about pagination behavior or result volume, which the schema partially compensates for.
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?
Three short sentences with the resource description front-loaded, followed by practical usage and then the API mapping. There is little waste; the trailing 'LGL: GET /api/v1/groups' is arguably redundant but is brief and aids traceability to the vendor API.
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 read-only two-parameter list tool with no output schema, the description covers what is returned (ids, keys, examples), why it matters (recording gifts, filtering searches), and the source endpoint. Only the lack of pagination/volume expectations keeps it from being fully complete.
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?
Schema description coverage is 100% and both parameters (limit, offset) are fully documented in the schema, including defaults and ranges. The description adds no parameter-level detail, so the baseline 3 applies.
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 specific resource (constituent groups with examples Board Member, Staff, Volunteer) and states what is returned (ids and keys), which makes the operation unambiguous. It stops short of an explicit verb like 'list' and does not differentiate itself from the closest sibling, lgl_list_type_values, which could look similar to an agent scanning names.
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?
The sentence 'Use the ids and names when recording gifts or filtering searches' explains what the results are good for downstream, which implies when the tool is relevant. However, there is no guidance on when to call this vs. a sibling list/search tool, and no exclusions or prerequisites are stated.
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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