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list_facets

Read-onlyIdempotent

List the full filter vocabulary: every facet value currently on the wire, across every key — lang, country, region, domain, topic, severity, provider, coverage and place — as one flat list with a signal count each, and a human-readable label for place ids. Every value it returns is a value scope_signals will accept right now.

This is the exhaustive listing and it is long, running to a hundred-odd values on a busy wire. If all you need is to pick a domain and a topic, get_facet_manifest answers that in a fraction of the tokens; come here when you need a value the manifest does not carry, or the counts behind one. Place facets are gazetteer ids; filter them by name with scope_signals rather than by the raw id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already set readOnlyHint=true, and the description adds valuable behavioral context beyond that: it warns that the listing is exhaustive and can be a hundred-odd values, guarantees that every returned value is directly acceptable by scope_signals, and explains that place facets are gazetteer IDs with human-readable labels. This sets expectations for length and response content.

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 multi-sentence, but each sentence earns its place: purpose, guarantee of compatibility, length warning, routing to the alternative, and the place-ID caveat. It is front-loaded and free of tautology, making even the lengthy-warning meaningful rather than redundant.

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?

For a zero-parameter, read-only tool with no output schema, the description fully compensates: it states exactly what the response contains, how long it can be, how the tool fits into the wider API, and how to use the results with scope_signals. The agent has enough context to invoke the tool correctly and interpret its result confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero properties and no required fields, so there are no parameters to explain. The baseline for 0 params is 4, and the description rightly does not invent parameter guidance. It further mentions the output structure enough for the absence of parameters to be non-blocking.

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 opens with a specific verb and resource ('List the full filter vocabulary'), explicitly enumerates all covered keys, and describes the exact output shape (flat list with a signal count each, plus a human-readable label for place ids). It also distinguishes itself from get_facet_manifest by naming itself as the exhaustive listing, so an agent can tell them apart without looking at any schema.

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use/when-not-to-use guidance: use get_facet_manifest when only a domain and topic are needed to save tokens, and list_facets when the manifest lacks a value or counts are needed. It also instructs how to handle place facets (filter by name via scope_signals, not by raw id), which preempts a likely error.

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

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct operation: the two facet-listing tools are explicitly differentiated as quick manifest vs exhaustive listing, and search_signals vs scope_signals is cleanly split between lexical search and facet filtering. The billing/payment tools also form a clear lifecycle with no overlapping responsibilities.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern: get_* and list_* for reads, and action verbs like register_agent, open_payment, settle_payment, scope_signals, search_signals for operations. No mixed casing or inconsistent verb styles.

Tool Count5/5

15 tools is at the upper edge of the well-scoped range but each tool earns its place: five cover data retrieval, four cover discovery/metadata, and five cover identity/billing. No redundant or filler tools.

Completeness5/5

The surface covers the full workflow for the stated domain: discover vocabulary, search/scope the live wire, retrieve individual signals and related signals, compute fused products, register an identity, and purchase/activate a plan. The only apparent omissions, such as cancellation, are outside the described prepaid self-service flow.

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