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donate

Step 1 of the MCP donation flow. Required inputs: campaign_id, amount, and reasoning. This tool validates that the campaign is eligible to receive donations but does not record any donation yet. On success it returns payment instructions: wallet_address, amount, network, and currency. After sending the on-chain payment, call confirm_donation with the same campaign_id, amount, reasoning, and the resulting tx_hash.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYes
reasoningYes
campaign_idYesFull campaign_id UUID returned by search_campaigns. Do not abbreviate it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / campaign_id / description
      Added value: +"Full campaign_id UUID returned by search_campaigns. Do not abbreviate it."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states that no donation is recorded yet, only validation occurs, and lists the exact return fields (wallet_address, amount, network, currency). This gives the agent a clear picture of side-effects and output without prior annotation.

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 concise—three sentences—and front-loaded with the position in the flow ('Step 1'). It wastes no words, each sentence adds necessary context, and it is structured to flow from purpose to requirements to next steps.

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 description covers the flow, required inputs, validation behavior, return fields, and the next step. It does not mention error handling (e.g., what happens if the campaign is not eligible) or additional constraints, but given no output schema exists and the flow is clearly outlined, it is largely complete. Minor gap: lack of failure behavior.

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 33% (only campaign_id has a description). The tool description does not add semantics for amount or reasoning beyond restating their names; it only notes they are required and passed through to confirm_donation. It fails to compensate for the low schema coverage, leaving those parameters underspecified.

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 tool's function: validating campaign eligibility and returning payment instructions as step 1 of a donation flow. It explicitly says it does not record a donation, and contrasts with the sibling confirm_donation, making the purpose and scope unambiguous.

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?

It explicitly identifies itself as 'Step 1 of the MCP donation flow' and instructs the agent to call confirm_donation after the on-chain payment with the same parameters and the tx_hash. This provides clear when-to-use and next-step guidance, effectively differentiating from the sibling 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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