lookup_nasa_apod
Get NASA's Astronomy Picture of the Day (image, title, explanation). Use for content and educational agents.
Cost: $0.005–$0.05 USDC on Base per call.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query_string | No |
GoCreative Agent API
TDQS
B3.2/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses that the tool returns image, title, and explanation, and mentions a cost range. However, it does not discuss authentication requirements, rate limits, data freshness, or any potential side effects. For a read-only lookup, the disclosure is basic but adequate.
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 short and front-loaded, with the main purpose stated in the first two sentences. The added cost information is relevant. However, it could be improved by including a brief explanation of the parameter, which would make it more complete without adding much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one optional parameter, no output schema, and no annotations, the description provides enough context for a simple use case. However, the lack of parameter documentation and usage guidance leaves a gap in completeness, especially for an agent that may need to know how to customize the query.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'query_string' with a default, but the description does not explain its purpose or how to use it. With 0% schema description coverage, the description fails to add meaning beyond the schema, leaving the agent uninformed about parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and the specific resource 'NASA's Astronomy Picture of the Day', listing the returned data (image, title, explanation). While it differentiates the tool from many other lookup tools by naming a unique resource, it does not explicitly contrast it with sibling tools.
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 suggests use 'for content and educational agents', providing a general context. However, it gives no guidance on when not to use this tool, nor does it mention alternative tools for similar purposes. The usage guidance is implied but not comprehensive.
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
B3.2/5.0
Disambiguation2/5
The set is riddled with near-duplicates: lookup_reddit/scrape_reddit, lookup_wikipedia/scrape_wikipedia, lookup_dockerhub/scrape_dockerhub, lookup_steam/scrape_steam, enrich_googlereviews/enrich_reviews, lookup_ip/lookup_ipinfo, and multiple crypto-pricing tools (lookup_crypto, lookup_coingecko, bundle_crypto_360, scrape_binance, scrape_coinbase). Descriptions try to differentiate with phrases like 'heavier than' or 'same domain but with full thread parsing,' but the boundaries are fuzzy and an agent can easily pick the wrong one.
Naming Consistency4/5
Naming follows a fairly consistent prefix-based snake_case pattern (lookup_, scrape_, enrich_, bundle_, search_, ai_, data_) where the prefix denotes action weight and the noun identifies the target. Minor deviations exist: posts_x, ai_ask/pro/ultra (model-tier names instead of resources), sslstatus (missing underscore), and lookup_useragents_top are slightly off-pattern.
Tool Count1/5
172 tools is an extreme count, far beyond even the 50+ floor for a score of 1. This floods the agent's context and tool-selection space, making every call require a search through a massive list. While aggregation servers can justify more tools, this volume is unmanageable and every tool must be evaluated by the agent.
Completeness3/5
The surface is extraordinarily broad but unevenly deep: many sources have both a light lookup and a heavy scrape variant, while other areas have just a single shallow endpoint. There is no coherent domain with complete lifecycle coverage, and despite the huge catalog, common capabilities are still absent. The breadth prevents obvious gaps, but depth and coherence suffer.