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WillHeadlee

Little Green Light MCP Server

by WillHeadlee

submit_gift_for_review

Submit gifts, pledges, or goals to the Little Green Light Integration Queue for human review. Includes tribute details and constituent matching via name and email.

Instructions

Submit a gift, pledge, or goal to LGL's Integration Queue for human review, including tribute (honor/memorial) details. Provide first_name/last_name/email to match the constituent this belongs to. This does NOT write to LGL directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoConstituent's email, for matching
fund_nameNo
gift_dateNoYYYY-MM-DD
gift_noteNo
gift_typeNoGift, In Kind, Pledge, Other Income, In Honor of, In Memory of, Soft Credit, Matching, Installment
goal_dateNo
goal_nameNo
last_nameNoConstituent's last name, for matching
ask_amountNo
first_nameNoConstituent's first name, for matching
gift_amountNo
goal_statusNo
team_memberNo
check_numberNo
deposit_dateNo
payment_typeNo
tribute_nameNo"Honorary - General", "Memorial - General", or a named tribute
campaign_nameNo
gift_categoryNo
pledge_amountNo
payment_amountNo
write_off_dateNo
gift_event_nameNo
ack_mailing_dateNo
deposited_amountNo
external_gift_idNo
gift_appeal_nameNo
payment_intervalNoW, B, M, Q, S, or Y
projected_amountNo
write_off_amountNo
deductible_amountNo
gift_is_anonymousNoyes/no
pledge_start_dateNo
tribute_dedicationNo
ack_mailing_templateNo
installment_due_dateNo
tribute_honoree_nameNo
tribute_recipient_nameNo
tribute_recipient_emailNo
projected_minimum_amountNo
tribute_recipient_addressNo
auto_generate_installmentsNoyes/no
tribute_recipient_salutationNo
tribute_notification_templateNo
Behavior4/5

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

The description adds key behavioral context beyond annotations: it explicitly states that this does NOT write to LGL directly, which clarifies the non-read-only but non-destructive nature. Annotations indicate readOnlyHint=false, so the description's emphasis on queuing for review is valuable transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action and key nuances (tribute details, matching fields, no direct write). Every sentence serves a purpose with no extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the complexity (44 parameters, no output schema, no required params), the description fails to explain the submission queue process, error handling, or the purpose of many parameters. It is not complete enough for an agent to effectively invoke the tool without additional context.

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

Parameters2/5

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

With only 20% schema description coverage, the description must compensate for 44 parameters. It highlights first_name, last_name, email, and tribute details, but the vast majority of parameters remain unexplained. The description adds some meaning but is insufficient given the low schema coverage.

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 the verb (submit), the resource (gift, pledge, or goal), and the destination (Integration Queue for human review). It distinguishes from sibling tools like submit_note_for_review by specifying the exact entity types.

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 implies when to use this tool (for gifts, pledges, goals) and mentions providing matching fields. However, it does not explicitly state alternative tools for other entities or provide when-not-to-use guidance. The context of sibling tools helps, but the description itself lacks explicit usage boundaries.

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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