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Little Green Light MCP by usefulapi

List appeals

lgl_list_appeals
Read-only

Fundraising appeals (mailings, emails, asks) with campaign, date, financial goal, cost and active flag. Use the ids and names when recording gifts or filtering searches. LGL: GET /api/v1/appeals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of entries to return, 1-100. LGL's default is 25.
offsetNoStart at this entry (0-based). Use the previous page's next_item. Default 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=true), so the bar is lower. The description adds genuine context by enumerating what each appeal record contains (campaign, date, financial goal, cost, active flag) and naming the underlying endpoint, which is useful since there is no output schema.

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?

Two tight sentences with the resource description front-loaded and the redirect to downstream use second. No wasted clauses, though the endpoint citation is marginally redundant.

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?

With no output schema, the description usefully lists the fields returned, and the schema fully covers pagination. For a simple read-only list tool, this is close to complete; only sibling routing is absent.

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?

Schema description coverage is 100% for both limit and offset, including defaults and pagination semantics, so the schema does the heavy lifting. The description contributes no additional parameter meaning; baseline 3 applies.

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?

States a specific verb and resource (list fundraising appeals) and even clarifies the domain with example types (mailings, emails, asks), plus naming the key fields it carries. It does not explicitly differentiate itself from close siblings like lgl_list_campaigns or lgl_list_funds, but the appeal framing is distinct enough to identify.

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?

The description gives downstream guidance ('use the ids and names when recording gifts or filtering searches'), which implies why one would retrieve appeals, but never states when to call this versus alternatives or any prerequisite. Usage context is implied rather than explicit.

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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