Skip to main content
Glama

NASA Image of the Day — space & astronomy photos (nasaiotd)

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 readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description reinforces this with 'Read-only' and adds unique behavioral context: 'earnings settle non-custodially to your withdrawal address on release,' which clarifies the settlement mechanism beyond annotation fields. It does not contradict annotations, so no penalty.

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, dense sentence that front-loads the primary question ('how much I have earned and what is pending') and then lists the returned categories. It is informative without excessive verbosity, though it could be slightly restructured for readability. Every phrase contributes value, earning a strong score.

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 no parameters, a rich output schema (present, though not shown), and comprehensive annotations covering safety, the description fully covers what an agent needs: what data it returns and the read-only nature. It lists all major result categories, leaving no ambiguity about the tool's capability. It is complete for an agent to decide to call it.

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 coverage is 100% (the schema states 'No arguments'). Per the rubric, a baseline of 4 applies for tools with no parameters. The description adds no parameter-specific details because none are needed; it focuses on output semantics, which is appropriate.

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 explicitly states the tool's purpose: to check earnings and pending amounts. It enumerates the specific data returned (lifetime USDC, pending, unclaimed rewards, payout balance, buyer spend, reputation), making it distinct from sibling action-oriented tools. The verb 'check' and resource 'earnings' are clear and specific, avoiding any tautology.

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 makes the tool's use case obvious: querying one's earnings. It implies when to use it (whenever an agent needs earnings/balance information) but does not explicitly list alternatives or exclusions. However, the context of siblings being primarily actions (fund, open, attach) makes the read-only query role unambiguous, so it meets the 'clear context, no exclusions' bar.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.8/5.0
Disambiguation2/5

Several tools occupy overlapping roles: data_session_fund, data_session_funding_package, and data_session_attach_escrow all handle payment for the same data listing, while a2awire_guide and get_recommended_action both provide navigation guidance. Descriptions clarify some sequencing, but an agent could easily misselect among the payment/session tools. The boundary between onboarding tools (register, onboard_start, get_recommended_action) is also fuzzy.

Naming Consistency2/5

Most tools use snake_case, but the verb/object order is inconsistent: data_session_* tools are object-first (data_session_open, data_session_query), while most others are verb-first (check_earnings, discover_agents, verify_contract). There are also one-off forms like a2awire_guide, data_preview, register, and hire_and_execute that break the pattern. The naming is readable but not predictable.

Tool Count2/5

16 tools is excessive for a server presented as 'NASA Image of the Day — space & astronomy photos,' since most tools are unrelated marketplace, escrow, and onboarding machinery. Only data_preview and the data_session_* tools actually serve the NASA image domain. The count may fit a broader A2AWire platform, but it is disproportionate to the server's stated purpose.

Completeness2/5

The actual NASA image surface is thin: data_session_query is the only retrieval tool and it requires a multi-step paid session setup. More importantly, find_paid_work explicitly tells agents to call start_job, but no start_job tool exists, creating a dead end in the advertised workflow. The set also lacks direct tools for browsing images or managing sessions after opening them.

Resources