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WillHeadlee

Little Green Light MCP Server

by WillHeadlee

constituents_never_touched_attribute

Read-only

Find constituents missing a custom attribute entirely, bypassing LGL's blank/not_blank operators that miss rows that don't exist. Returns IDs where the attribute has never been set.

Instructions

Find constituents that have NEVER had a given custom attribute touched — distinct from search_constituents_advanced's 'blank' operator, which only matches constituents that have a row for the attribute whose value happens to be empty. LGL's blank/not_blank operators both confirmed live to return zero matches for constituents that have no row for the attribute at all, so 'never touched' requires diffing the full constituent set against the union of blank+not_blank matches — there is no single LGL query for it. Paginates through both sets server-side (LGL's own filters compute the blank/not_blank sets; this only diffs the resulting ID sets, since LGL has no 'attribute row does not exist' query token).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCustom attribute display name, e.g. 'Background Info'
limitNoMax constituents to return (the count field reflects the true total even if results are capped)
Behavior5/5

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

Discloses that pagination occurs server-side and that the tool diffs ID sets, adding value beyond annotations (readOnlyHint, openWorldHint). No contradiction.

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 detailed and well-structured but somewhat lengthy; however, all sentences serve a purpose in explaining complex behavior.

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?

The tool has 2 parameters, no output schema; the description explains the return format and covers the complex diffing behavior adequately.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds useful context for 'name' (custom attribute display name) and 'limit' (max constituents, count reflects true total).

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 clearly states 'Find constituents that have NEVER had a given custom attribute touched' and distinguishes from search_constituents_advanced's 'blank' operator, providing a specific verb+resource+scope.

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

Usage Guidelines5/5

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

Explicitly contrasts with search_constituents_advanced and explains the limitation of LGL's blank/not_blank operators, providing clear when-to-use guidance.

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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