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Starwell: World Data & Statistics

Get observations (with provenance)

get_observations
Read-only

Observation values for one series. Every value carries provenance (the exact source URL it came from, retrieval time, connector version) and the envelope carries the series verification status + citation. Defaults to the latest 60 points; use start/end (YYYY-MM-DD) or latest to control the window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoYYYY-MM-DD inclusive upper bound
startNoYYYY-MM-DD inclusive lower bound
latestNoReturn only the latest N points (default 60 when no start/end given)
sourceYes
seriesIdYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the agent knows it's safe. The description adds valuable behavioral context: every value carries provenance (source URL, retrieval time, connector version) and the envelope includes verification status and citation. It also discloses the default 60-point window and the ability to override it, which is beyond what annotations provide.

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 two sentences, front-loaded with the core purpose, then adding concise detail on provenance, verification, and window control. Every sentence contributes value; no filler or redundancy.

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?

Given the tool's simplicity (read-only, 5 params, no output schema), the description covers key aspects: what data is returned (provenance, verification status, citation), default behavior (60 points), and how to control the window. It could mention pagination or response size limits, but the schema already documents the maximum 'latest' value.

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 60% (start, end, latest have descriptions; source and seriesId do not). The description reinforces the window semantics ('start/end (YYYY-MM-DD) or latest') but does not identify or explain source or seriesId. It partially compensates but does not fully cover all parameters.

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's purpose: 'Observation values for one series.' This is a specific verb+resource pairing that distinguishes it from siblings like get_series (metadata) and get_series_stats (statistics). The additional detail about provenance and verification status further clarifies scope.

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 provides clear context for use: it retrieves observation values for a single series, with control over the time window via start/end or latest. It does not explicitly state when not to use it or mention alternative tools, but the use case is unambiguous given the sibling names.

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

B3.4/5.0
Disambiguation5/5

Each tool targets a distinct operation: Q&A, deep analysis, series metadata, observations, stats, catalog search, and monitor CRUD. The only potential overlap between answer and deep_analysis is explicitly disambiguated by use-case guidance, and delete_monitor is unambiguous by name even without a description.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern (get_*, list_*, create_*, delete_*, search_*). However, 'answer' and 'deep_analysis' deviate from this pattern, making the naming convention slightly inconsistent.

Tool Count5/5

With 11 tools, the server is well-scoped for a world data/statistics domain. It covers discovery, retrieval, analysis, and monitoring without unnecessary bloat, and each tool earns its place in the set.

Completeness5/5

The toolset provides a complete workflow: discover sources/datasets via list_sources/list_datasets/search_catalog, retrieve series/observations/stats via get_*, analyze via answer/deep_analysis, and manage monitors via create/list/delete_monitor. No critical operations are missing for the stated purpose.