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WillHeadlee

Little Green Light MCP Server

by WillHeadlee

get_donor_context

Read-only

Retrieve a donor's full profile, recent giving history, group memberships, and notes in one lookup, eliminating multiple round trips.

Instructions

One-shot lookup that returns a constituent's profile plus their recent giving history, group memberships, and recent notes. Saves 4-5 round trips compared to calling get_constituent + list_gifts + list_group_memberships + list_notes separately for the common 'tell me about ' workflow. Accepts either constituent_id (preferred) or name (resolved via search; errors with candidates if multiple constituents match). Writes an 'AI Access Log' note directly to that constituent's record noting when and by which tool it was accessed — this happens automatically in full and assisted (LGL_ASSISTED_MODE=true) modes, and is silently skipped under strict LGL_READ_ONLY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName to resolve via search if ID isn't known. Errors with a candidate list if multiple constituents match.
gift_limitNoMax recent gifts to include
note_limitNoMax recent notes to include
constituent_idNoDirect lookup by ID (preferred if known)
Behavior1/5

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

The description reveals that the tool writes an 'AI Access Log' note to the constituent's record, which contradicts the readOnlyHint annotation. According to the rules, a contradiction with annotations yields a score of 1, even though the description itself is transparent about the behavior.

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 relatively long but front-loaded with the core purpose. Every sentence adds value, covering the side effect and usage nuance. Could be slightly more concise, but the detail is warranted.

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?

Given the complexity (4 params, no output schema), the description explains the returned data (profile, gifts, memberships, notes) and the behavioral nuances (ID vs name, side effect). It provides sufficient context for proper invocation.

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

Parameters5/5

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

Schema coverage is 100%, and the description adds significant meaning beyond the schema: it explains that name is resolved via search, constituent_id is preferred, and that name may return candidate errors. It also clarifies the defaults and purpose of gift_limit and note_limit.

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 it is a 'one-shot lookup' that returns a constituent's profile, recent giving history, group memberships, and notes. It explicitly distinguishes from siblings by noting it saves round trips compared to calling multiple separate tools like get_constituent and list_gifts.

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

Usage Guidelines4/5

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

The description explains when to use it ('tell me about <donor>') and contrasts with separate calls. It also notes that name can be used but may error with candidates. However, it does not explicitly state when not to use it or provide alternative tools.

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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