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TensorFeed

by ai.tensorfeed

get_recent_earthquakes

Get recent earthquakes from the US Geological Survey's pre-built summary feeds. Choose a magnitude bucket (significant | 4.5 | 2.5 | 1.0 | all) and a time window (hour | day | week | month). Returns a flattened list with id, magnitude, place, time (ISO 8601), depth_km, longitude, latitude, tsunami flag, USGS detail URL. Upstream feeds refresh every minute. License: US Government public domain (17 USC §105).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax earthquakes to return (1-500). Default 50.
periodNoTime window. One of: hour, day, week, month. Default day.day
magnitudeNoMagnitude bucket. One of: significant, 4.5, 2.5, 1.0, all. Default 4.5.4.5

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description discloses important behaviors: refresh rate (every minute), license (public domain), and return format (flattened list with specific fields). It does not mention rate limits, authentication, or error handling, but for a read-only data feed this is adequate.

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?

The description is four sentences, each serving a purpose: purpose, parameter selection, return format, and additional info. It is front-loaded with the main action and is free of unnecessary words.

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 no output schema, the description sufficiently explains the return fields (id, magnitude, place, time, depth, coordinates, tsunami flag, URL). It also covers data source, refresh rate, and licensing. Missing details like error handling are not critical for this simple query 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 description coverage is 100%, so the baseline is 3. The description reiterates parameter options (magnitude bucket values, time window values) and implicitly mentions limit via the return format, but adds minimal new meaning beyond the schema's own parameter 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 recent earthquakes from USGS summary feeds, specifying the source and type of data. Among sibling tools like get_weather_alerts or get_news_articles, this is uniquely about earthquakes, so purpose is unambiguous.

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 how to choose magnitude and time window parameters, providing explicit options. However, it does not discuss when to avoid this tool or compare it to alternatives; given the sibling tools are unrelated, usage is clear but lacks explicit exclusions.

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
Disambiguation3/5

Several security/vulnerability tools (check_ai_supply_chain_risk, get_cve_record, get_osv_advisory_by_id, get_osv_advisory_for_package) have overlapping purposes, making it potentially confusing to choose the right one. Other tools are more distinct, but the ambiguity in this cluster lowers the score.

Naming Consistency3/5

All names are snake_case and mostly follow a verb_noun pattern, but the verbs are inconsistent (check, get, list, lookup, query, register, route, search, submit, whats_new). Some tools use 'get' while others use 'check' for similar retrieval actions, and 'whats_new' does not fit the verb_noun pattern.

Tool Count2/5

With 27 tools, the count exceeds the 25 threshold for 'too many', even though the broad scope spans many domains. The sheer number makes the server feel heavy and harder to navigate.

Completeness3/5

The server covers a wide range of data domains, but notable gaps exist: no management of watch subscriptions (only register), no CVE search, and no model search. Write operations are minimal, leaving some workflows incomplete.

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