ground_truth
The bundled five-question answer (water / stability / hazard / resource / provability) + one provenance record.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | ||
| lon | Yes |
The bundled five-question answer (water / stability / hazard / resource / provability) + one provenance record.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | ||
| lon | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that the result includes a five-part answer plus provenance, but it does not clarify open-world behavior such as potentially missing answers or the shape of the provenance record. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence with no filler and every phrase carries meaning. It would be stronger if it started with an explicit action verb, but it is appropriately sized and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only lookup, the description names the output bundle clearly enough. However, with no output schema, it leaves gaps around response structure, whether individual answers can be null under open-world conditions, and any coordinate system assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention lat, lon, coordinate system, valid ranges, or any other parameter semantics. The schema's lat/lon names are self-explanatory, but that meaning comes from the schema, not the description, which adds no parameter-level value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource—the bundled five-question ground truth answer—and enumerates its components (water / stability / hazard / resource / provability) plus a provenance record. It lacks an explicit verb like 'retrieve' or 'return', but the noun-phrase framing is still clear and the word 'bundled' differentiates it from individual sibling tools like ground_stability or water_availability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings. It does not say 'use this when you need all five answers at once' or mention any alternatives such as ground_stability, seismic_hazard, or water_availability for single-question lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
ground_truth aggregates the same water/stability/hazard/resource answers offered by individual tools, and check_hypothesis/verify/list_nulls all inhabit the trust/provenance space, so an agent may hesitate between options. The descriptions are detailed enough to resolve most selections, but the overlap is real and not just one or two edge cases.
All names use snake_case, but the style is mixed: some are bare nouns or noun phrases (capabilities, ground_stability, water_availability) while others are imperative verbs (check_hypothesis, list_nulls, run_controlled_test, verify). This is readable but lacks a single consistent verb_noun convention.
Eleven tools is a well-scoped size for an Earth-grounding service; each tool earns its place by covering a distinct capability like querying hazards, checking hypotheses, running controlled tests, or verifying anchors. The set is neither bloated nor thin.
The set covers the advertised five-question answer surface plus verification, hypothesis checking, nulls, and space-weather risk, giving agents a solid query-test-verify lifecycle. Minor gaps exist around contributing new nulls or hypotheses, but the core workflows have no dead ends.