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Prepare MoonPay top-up

prepare_moonpay_onramp
Read-onlyIdempotent

Use this when a person funding one canonical Base bounty needs Base USDC. Prepare a first-party MoonPay handoff only; never request card data or identity documents in ChatGPT, never treat a MoonPay purchase as bounty funding, and require a separate canonical funding authorization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intent_idNoOptional hosted funding-intent identifier to preserve the return boundary.
bounty_contractYes
amount_base_unitsYesPlanned bounty contribution in 6-decimal USDC base units.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYes
stateYes
networkYes
sandboxYes
providerYes
intent_idYes
onramp_urlYes
next_actionYes
bounty_fundedYes
schema_versionYes
bounty_contractYes
checkout_createdYes
evidence_boundaryYes
purchase_completedYes
planned_amount_usdcYes
canonical_funding_eventYes
planned_amount_base_unitsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive behavior, and the description adds meaningful policy context: it only produces a first-party handoff, must not collect sensitive data, and must not conflate a purchase with funding. No contradiction with annotations.

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?

One dense sentence that front-loads the trigger condition and then states hard constraints. No filler or repetition of schema/annotation information.

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

Completeness5/5

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

For a 3-parameter tool with an output schema and safety annotations, the description covers trigger, scope, authorization requirement, and misuse prevention. An agent has what it needs to use the tool correctly.

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

Parameters3/5

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

With 67% schema coverage and no explicit parameter explanations in the description, the required bounty_contract and amount_base_units rely on their names and the schema pattern/min-max. The description's Base USDC context supports amount_base_units, but it does not add detail about units or the contract's role.

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 names a specific action (prepare a first-party MoonPay handoff) and a specific trigger (person funding one canonical Base bounty needs Base USDC), which clearly separates it from sibling prepare_bounty_action/post tools. It also uses 'only' to delimit the tool's 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?

It gives an explicit when-to-use condition ('Use this when a person... needs Base USDC') and explicit prohibitions ('never request card data... never treat a MoonPay purchase as bounty funding... require a separate canonical funding authorization'). This tells an agent when and when not to invoke the tool.

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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TDQS

A3.9/5.0
Disambiguation3/5

Most tools are distinct by domain (comments, feeds, on-ramp, competitions), but prepare_bounty_action and prepare_bounty_post both trigger on an approved posting flow, and list_autonomous_bounties vs get_bounty_feed vs inspect_open_competition_v2 present overlapping read surfaces. The long 'use this when' guards help, but an agent could still select the wrong prepare or list tool.

Naming Consistency4/5

The names are almost uniformly snake_case verb_noun with predictable prefixes like prepare_, get_, and list_. Minor inconsistencies: add_bounty_comment vs list_bounty_comments (singular/plural), the v2 suffix, and compile_objective_with_cloud_agent breaks the concise verb_noun pattern.

Tool Count4/5

Thirteen tools is within the normal range for a platform covering bounty lifecycle, comments, feeds, competitions, and fiat on-ramp. However, the generic prepare_bounty_action plus separate prepare_bounty_post and several read/list variants make the set feel slightly heavier than the core domain needs.

Completeness4/5

The core bounty lifecycle (post, fund, solve/claim, complete, verify), status checks, listing, comments, and sharing are all represented. Missing explicit update/cancel or single-bounty detail operations are minor gaps because the prepare/status model and feed data cover most agent workflows.

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