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nearby

Entities near a location (the primitive look_from builds on). Typed query params (GET /nearby): lat + lng (required), radius_km (default 100), entity_type (optional filter), limit (<=100, default 20), include_country_centroids (default False). Metered — debited from the CALLING agent's own wallet, not the owner's (read it with the joules_balance tool). For the exact per-caller price before you call, use the billing_quote tool (free, tier-aware; returns joules_all_in) or check affordability with the joules_deficit tool; the true debit is the base joule_cost plus a 0.5% rail surcharge rounded up (a 100 J call debits 101 J) = joules_all_in. Carries source_tier/tier_label. ⚠ CHARGING: the meter RESERVES before the query runs and SETTLES after delivery for what was actually delivered (an empty result settles to 0; a partial traversal settles for the hops delivered; a 4xx releases the reservation). An abandoned or timed-out call still settles once the backend delivers. A replay is served free only for the SAME credential + SAME idempotency key + SAME request within 15 minutes — a different payer is a different payer. Every call through this relay carries a fresh key, so a retry here is always a new charge. Price with billing_quote first; verify any charge with the billing_attempts tool (own wallet: reserved vs settled, per attempt). WHAT YOU PAID: the JSON response carries a top-level charged_joules — the all-in PRICE of this call — and a metering block written AFTER the settle has run: {attempt_id, settlement, settled_joules, check}. metering.settlement is whether you PAID: settled · settled_zero (empty result, nothing moved) · settle_failed (delivered but UNPAID — the wallet is then locked until it clears; the next metered call 402s naming the attempt, the amount and what clears it) · released (4xx/5xx, nothing moved) · unknown. settled_joules is what actually left the wallet (0 unless settled). A cached replay carries no block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lngYes
limitNo
radius_kmNo
entity_typeNo
include_country_centroidsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "nearbyDictOutput",
+  "type": "object"
+}
  2. First observed

TDQS

B3.2/5.0
Behavior5/5

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

The description goes into exceptional detail about the metering and charging behavior: reservation, settlement, what happens on empty results, partial traversal, 4xx responses, abandoned calls, and replay conditions. It also explains the `metering` block and `charged_joules` fields. Since no annotations are provided, this thorough disclosure of cost behavior is highly valuable and exceeds the burden of transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and heavily weighted toward billing details, which are important but could be summarized more concisely. It is structured into sections (params, metering, payment) which aids readability, but the length may overwhelm an agent looking for core functionality. Every sentence is informative, but the overall density reduces conciseness.

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?

The description thoroughly covers the billing and metering aspects, but it omits functional details such as what the returned entity data looks like (beyond the metering block), how results are ordered, and what entity_type values are valid. Given the tool has an output schema, the description does not need to enumerate the full response, but it should at least mention the nature of the entities returned. The billing focus leaves the core query behavior underdescribed.

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?

The description lists all six parameters and adds constraints (radius_km default 100, limit <=100 default 20, include_country_centroids default False). However, it does not explain what entity_type accepts (no enums or examples) or what include_country_centroids actually does. With 0% schema description coverage, it partially compensates but leaves key semantics unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool returns 'Entities near a location' and references it as the primitive `look_from` builds on, which gives a general sense of purpose. However, it lacks a direct verb like 'find' or 'list', and does not specify what constitutes an entity or what the response looks like beyond the metering fields. It also does not differentiate it from sibling tools like `look_at` or `hops`.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 alternatives. It mentions that `look_from` builds on it but does not explain when to choose `nearby` over `look_from` or any other related tool. There is no statement about use cases, exclusions, or preferred conditions.

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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