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Nasa

by io.github.pipeworx-io

Get Apod

get_apod
Read-onlyIdempotent

Get the NASA Astronomy Picture of the Day with explanation. Optionally specify a date. Example: get_apod({ date: "2024-01-15", _apiKey: "DEMO_KEY" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate in YYYY-MM-DD format (optional, defaults to today). Range: 1995-06-16 to today.
_apiKeyNoNASA API key (optional, defaults to DEMO_KEY — get a free key at api.nasa.gov)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to the astronomy picture
dateYesDate of the astronomy picture in YYYY-MM-DD format
titleYesTitle of the astronomy picture
hd_urlNoURL to the high-definition version of the picture
copyrightNoCopyright information for the picture
media_typeYesType of media (image or video)
explanationYesExplanation of the astronomy picture

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description's addition of 'with explanation' and the example add context but do not significantly enhance behavioral understanding beyond annotations. No contradictions.

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?

Two sentences plus an example, with no wasted words. The most critical information (what it does and the optional date) is front-loaded.

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 existence of an output schema (handling return values), the description completely covers what an agent needs to know: it retrieves APOD with explanation, optionally for a date. Examples further aid understanding.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description reinforces optionality and provides an example, but does not add new meaning beyond the schema's descriptions.

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 clearly states the tool retrieves the NASA Astronomy Picture of the Day with an explanation, and the name and title reinforce this. It is distinct from sibling tools like get_asteroids or get_mars_photos, which focus on different NASA data.

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 explains when to use the tool (to get APOD) and mentions the optional date parameter. However, it does not explicitly state when not to use it or provide alternatives, though siblings are sufficiently different that guidance is less critical.

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

A3.6/5.0
Disambiguation2/5

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta (currently identical), and ask_pipeworx_grounded are three variants of the same router, while bet_research, polymarket_edges, and polymarket_arbitrage all target prediction-market opportunities. The descriptions are detailed, but an agent must read extensively to avoid selecting the wrong tool within each cluster.

Naming Consistency2/5

Naming is a mix of conventions: get_*/search_* for NASA tools, ask_pipeworx_* and polymarket_* family prefixes, plus one-off names like entity_profile, bet_research, deep_research, recent_changes, and scan_dependency. There is no consistent verb_noun or family-wide pattern, making tool selection unpredictable despite each individual name being readable.

Tool Count2/5

36 tools is heavy for a server named Nasa, and only 5 of them are actually NASA-related; the rest form a sprawling general data-research, prediction-market, memory, and subscription toolkit. The count is borderline defensible for a broad data assistant, but it is clearly unjustified under the server's stated NASA identity.

Completeness3/5

As a general data-research assistant the surface is quite complete: discovery, routing, grounded verification, entity profiles, comparisons, memory, subscriptions, and feedback are all covered. As a NASA server, however, there are notable gaps—no EONET events, Earth observation, exoplanet archive, or TLE/mission-specific data—and the large non-NASA tool surface does not fill those gaps.

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