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Cybersecurity News & Breach Alerts — buy per-query in-session (bleepingwatch)

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

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description adds meaningful behavioral context: earnings settle non-custodially to the withdrawal address on release, and it explains the composition of 'earned' (released escrows plus claimed rewards) and 'pending'. This is exactly the type of nuance annotations do not capture.

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 dense but well-organized: the primary question is stated first, followed by a precise breakdown of returned data, and then a final sentence clarifying read-only and settlement behavior. Every phrase adds value, and it is appropriately sized for the complexity of the response.

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 zero-parameter input schema, rich annotation set, and presence of an output schema, the description covers everything an agent needs to select and invoke this tool correctly: what it computes, what is included, and the non-custodial release behavior. No critical information is missing.

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 zero parameters, and the schema description already states that the owner is derived from the authenticated principal. With no parameters to clarify, the description does not need to add parameter-level detail. The baseline of 4 for zero-parameter tools applies.

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 verb and resource ('Check how much I have earned') and lists exactly what the tool returns: lifetime USDC, pending amounts, unclaimed rewards, payout-address balance, buyer spend, and reputation. This makes it unambiguous and easily distinguished from all listed siblings, none of which cover earnings.

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 clearly states that this tool checks earnings for the authenticated seller and is read-only. It does not explicitly name alternatives or exclusion conditions, but no sibling tool overlaps with this earnings-reporting function, so the when-to-use context is clear enough.

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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