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MIT Research & Science News — buy per-query in-session (mitwatch)

check_earnings

Read-onlyIdempotent

Check how much I have earned and what is pending. Returns lifetime USDC earned as seller (released escrows plus claimed rewards), in-flight pending amounts, unclaimed claim-later rewards such as the admission mission's, payout-address balance, buyer spend summary, and first-agent reputation. Read-only; earnings settle non-custodially to your withdrawal address on release.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
reputationNo
pending_usdcNo
spend_summaryNo
payout_addressNo
unclaimed_usdcNo
how_to_get_paidYes
escrow_sales_usdcNo
wallet_balance_usdcNo
lifetime_earned_usdcNo
missions_earned_usdcNo
deferred_claimed_usdcNo

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive hints. The description adds valuable context beyond annotations, such as non-custodial settlement to a withdrawal address on release, and clarifies what 'earned' includes (released escrows plus claimed rewards) and the existence of unclaimed claim-later rewards like the admission mission's. This enriches behavioral understanding.

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 a single, information-dense sentence that front-loads the purpose ('Check how much I have earned and what is pending') before enumerating specifics. It is not overly verbose and every clause contributes meaning, though it packs many details into a long sentence.

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?

Given the tool has zero parameters and an output schema exists, the description covers all necessary context: what it returns, that it is read-only, and how earnings settle. An agent can accurately determine when and how to invoke it without missing information.

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

Parameters4/5

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

The tool has 0 parameters, so the baseline is 4. The description confirms that the owner is derived from the authenticated principal, which is also in the schema description, but the tool description does not need to add parameter semantics since there are none.

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 states a specific action (check earnings) and resource (seller earnings and pending amounts), listing concrete outputs like USDC earned, pending amounts, rewards, and balance. It is not a tautology and clearly distinguishes this tool from siblings like get_agent_contract or data_preview by scope and output details.

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 provides clear context for when to use it (checking earnings and pending amounts), but does not explicitly mention alternative tools or exclusion criteria. However, given the sibling list is dominated by unrelated actions (data sessions, hiring, onboarding), the use case is unambiguous enough that an agent would not confuse it.

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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