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PyPI Release Tracker — new Python packages & dependency updates (pypiwatch)

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 declare readOnly, idempotent, non-destructive. The description adds meaningful behavioral context beyond those: 'earnings settle non-custodially to your withdrawal address on release.' It also clarifies the composition of lifetime USDC. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a dense two-sentence paragraph with no filler. The main purpose is front-loaded, and the return-value breakdown follows logically. Slightly long, but every clause earns its place given the range of data covered.

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 zero-parameter read-only tool without an output schema, the description fully covers what the agent will receive and how earnings behave. The settlement note and the enumeration of return categories leave no critical ambiguity.

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?

There are zero parameters, and the schema already explains 'No arguments — the owner is derived from the authenticated principal.' The description doesn't need to add parameter semantics; it focuses on return contents instead.

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 uses a specific verb ('Check') and resource ('earnings'), then enumerates exactly what that includes: lifetime USDC, pending amounts, unclaimed rewards, payout balance, buyer spend summary, and reputation. This is distinct from the sibling tools, which concern contracts, work discovery, and onboarding.

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 opening phrase 'Check how much I have earned and what is pending' gives clear context for when to invoke the tool. It doesn't explicitly state when not to use it or name alternatives, but the scope is specific enough to route an agent appropriately.

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

B3/5.0
Disambiguation1/5

Multiple tools are near-duplicates in the data-session funding flow (data_session_fund, data_session_funding_package, data_session_attach_escrow) and guidance tools overlap (a2awire_guide vs get_recommended_action). A caller looking for PyPI release information cannot easily distinguish the relevant query tools from the marketplace and onboarding tools.

Naming Consistency2/5

There is a data_session_* cluster and some get_* names, but the set mixes bare verbs (register), gerund-style names (check_earnings, find_paid_work), compound verbs (hire_and_execute), and prefixed nouns (a2awire_guide, onboard_start). The naming is not chaotic enough for 1, but it lacks a consistent convention.

Tool Count2/5

16 tools is already on the heavy side, and the majority concern agent-marketplace onboarding, escrow, hiring, and earnings rather than PyPI package tracking. The count would be plausible for an A2AWire platform server, but it is far too large and unfocused for the advertised PyPI Release Tracker.

Completeness1/5

The stated purpose is tracking new PyPI releases and dependency updates, yet there are no dedicated tools for listing packages, fetching release details, or monitoring dependencies. The only data-related surface is a generic data_preview/data_session_query pair, leaving the actual domain essentially uncovered.

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