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Create giving intent

create_giving_intent
Read-onlyIdempotent

NO-CHARGE deep-link giving handoff (Phase 3 MVP). Returns mode=deep_link, org donate_url, donation_proof=null, charge=false. Did It Work? never processes payment, stores cards, or calls Stripe. Optional modeled_impact is modeled≠guaranteed. Prefer GET; POST accepts the same fields as JSON body.

Input Schema

NameRequiredDescriptionDefault
org_idYes
vehicleNodirect_cash
amount_usdYes
include_impactNoWhen true, attach modeled_impact (MODELED, NOT GUARANTEED)
values_profile_idNovp_anonymous

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already state readOnlyHint, idempotentHint, and non-destructive behavior, so the description's added value is in clarifying what does not happen: no payment processing, no card storage, no Stripe calls, donation_proof=null, and modeled impact is not guaranteed. That is meaningful behavioral context beyond annotations, though rates, side effects, and idempotency details are left to annotations.

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 short, front-loaded, and mostly dense with useful facts. Some phrasing such as 'Did It Work?' and 'Phase 3 MVP' is internal shorthand that slightly reduces clarity, but there is little waste.

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

Completeness3/5

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

For a 5-parameter tool with no output schema, the description does describe the return shape and the no-charge handoff clearly. However, it omits most parameter semantics and provides weak usage guidance, so it is only minimally complete for correct invocation.

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?

Schema description coverage is only 20%, so the description carries most of the parameter burden but explains only include_impact indirectly via 'Optional modeled_impact is modeled≠guaranteed.' It says nothing about org_id, amount_usd, vehicle enum, or values_profile_id, leaving most required inputs undocumented.

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?

The description states a specific action and outcome: a no-charge deep-link giving handoff that returns mode=deep_link, donate_url, and charge=false. It is clearly distinct from sibling tools like allocate_portfolio or recommend_charity, though the 'Phase 3 MVP' phrasing adds noise rather than precision.

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

Usage Guidelines2/5

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

The only usage guidance is 'Prefer GET; POST accepts the same fields as JSON body,' which is a transport note rather than when-to-use guidance. It does not say when an agent should choose this tool over alternatives or what prerequisites apply.

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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