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Nasa

by io.github.pipeworx-io

Get Solar Flares

get_solar_flares
Read-onlyIdempotent

Get recent solar flare events from NASA DONKI space-weather data. Returns each flare's class (e.g. C4.0, M1.8, X1.2), begin/peak/end times, source region, and active region number. Use for "recent solar flares", "is there solar activity / a solar storm", space-weather questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoNASA API key (optional, defaults to DEMO_KEY)
end_dateNoEnd date YYYY-MM-DD (optional; default today).
start_dateNoStart date YYYY-MM-DD (optional; default ~30 days ago).

TDQS

A4/5.0
Behavior3/5

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

Annotations (readOnlyHint, idempotentHint, destructiveHint) already indicate safe, read-only behavior. Description adds no behavioral details beyond the annotations, but does not contradict them.

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, no fluff. First sentence states purpose and return data, second provides usage examples. Efficient and front-loaded.

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?

Covers what is returned and typical use cases. Lacks mention of default date ranges (handled by schema). Overall complete for a simple read-only tool.

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%, and description does not add parameter details beyond the schema. Baseline score of 3 applies per rules.

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?

Description clearly states the tool gets recent solar flares from NASA DONKI data, lists returned fields (class, times, source region, active region number), and provides example queries. Differentiates from siblings like get_apod and get_asteroids by focusing on space-weather 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?

Explicitly describes when to use (e.g., 'recent solar flares', 'is there solar activity / a solar storm'). Does not mention when not to use or alternative tools, but context makes it clear this is for space-weather queries.

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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