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get_facet_manifest

Read-onlyIdempotent

Read the shape of the wire in one small response: a two-level tree of domain and the topics under it, each with a signal count, ranked so the busiest lead. This is the map to read first — read it once, choose a scope offline, then make one precise call to scope_signals or search_signals instead of guessing a filter.

It covers two facet keys only, domain and topic, and truncates the topic tail under each domain, so it stays short enough to read in full. When you need the rest of the vocabulary — the languages, countries, providers, severities, coverages and place ids you can also filter by, exhaustively and with counts — call list_facets instead. The manifest states structure, not signal content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses the two-key limitation, the truncation behavior ('truncates the topic tail under each domain'), the ranking order, and a negative scope ('The manifest states structure, not signal content'). These are exactly the behavioral traits an agent would be surprised by, and they are not in the structured hints.

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?

Each of the five sentences earns its place: purpose, usage workflow, limitation, alternative routing, and negative scope. The core purpose is front-loaded in the first sentence, and the detailed list of alternative facet keys is concrete rather than padding.

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 tool with no output schema, the description compensates well: it describes the response shape (two-level tree, signal counts, ranking), the truncation limitation, and what the response is not. The rich annotations carry the safety profile, so nothing an agent needs to call it correctly is missing.

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?

Zero parameters with 100% schema coverage, so the baseline is 4. The description correctly implies no inputs are needed and has no parameter semantics to clarify; nothing is missing here.

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?

States a specific verb and resource: 'Read the shape of the wire... a two-level tree of domain and the topics under it, each with a signal count, ranked so the busiest lead.' It explicitly contrasts with list_facets (the exhaustive version), so an agent can distinguish them without inspecting either 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?

Gives an explicit workflow: 'read it once, choose a scope offline, then make one precise call to scope_signals or search_signals instead of guessing a filter.' It also names the exact exclusion case and alternative: 'When you need the rest of the vocabulary... call list_facets instead.' Nothing is left to inference.

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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