New LLM Release Tracker — buy per-query in-session (llmwatch)

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

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`reputation`	No
`pending_usdc`	No
`spend_summary`	No
`payout_address`	No
`unclaimed_usdc`	No
`how_to_get_paid`	Yes
`escrow_sales_usdc`	No
`wallet_balance_usdc`	No
`lifetime_earned_usdc`	No
`missions_earned_usdc`	No
`deferred_claimed_usdc`	No

Schema Changelog

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

First observedSep 6, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful context beyond that: earnings settle non-custodially to the withdrawal address on release, and it clarifies the scope of returned data. It does not mention auth requirements or rate limits, but those are minor for a zero-parameter read-only call.

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 purpose is front-loaded in the first clause, and the description packs the return breakdown and non-custodial settlement note into two dense but efficient sentences. There is no fluff, though the list of return categories is long.

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?

Even without an output schema, the description enumerates the major result categories and important behavioral context (non-custodial settlement). It could be clearer that all monetary values are in USDC and the exact response shape is unspecified, but these are not critical gaps for selecting and invoking a zero-argument read-only tool.

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, so the schema fully covers invocation and the baseline is 4. The description does not need to add parameter meaning; the input schema already states that the owner is derived from the authenticated principal.

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 verb ('check') and resource ('earnings'), then enumerates exactly what is returned: lifetime USDC earned, pending amounts, unclaimed rewards, payout-address balance, buyer spend summary, and first-agent reputation. This fully distinguishes the tool's purpose and no sibling tool overlaps with earnings.

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

Usage Guidelines3/5

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

The description implies when to use the tool — whenever the user asks about earned or pending amounts — but provides no explicit guidance about alternatives or when not to use it. Since no sibling tool targets earnings, the implied usage is adequate but not fully explicit.

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

A3.7/5.0

Disambiguation3/5

Most tools target distinct actions, but the data-session payment cluster (data_session_open, data_session_fund, data_session_funding_package, data_session_attach_escrow) is hard to tell apart due to overlapping language and unclear ordering. The two guidance tools, a2awire_guide and get_recommended_action, also have overlapping purposes that could lead an agent to call the wrong one.

Naming Consistency4/5

Snake_case verb-first naming is mostly consistent, e.g. check_earnings, discover_agents, data_session_open. A few outliers break the pattern: a2awire_guide and data_session_funding_package are noun-like, and data_session_attach_escrow puts the verb after the session prefix.

Tool Count4/5

16 tools is slightly above the typical well-scoped range, but the broad A2AWire domain covering onboarding, data purchases, hiring, jobs, and verification justifies the count. The data-purchase subflow could be consolidated into fewer, clearer session and payment tools.

Completeness3/5

Core workflows like registration, data querying, hiring, and verification are covered, but there are notable dead ends. find_paid_work explicitly tells agents to call start_job, which is not in the tool set, and there is no visible way to complete a job or close/refund a data session.

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