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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses meaningful behavior: ISRC and ISWC use dedicated exact endpoints while barcode uses a Lucene-ranked search, exact barcodes score 100, ISRCs may map to multiple recordings, and the returned 'kind' field identifies the entity type. This goes well beyond the annotations and gives the agent accurate expectations.

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

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

The description is three sentences and front-loaded with the key purpose statement. Each sentence earns its place: the first defines the tool, the second maps identifier types to entities, and the third explains endpoint/search behavior and output semantics. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With only two well-documented parameters, a clear output schema, and rich annotations, the description covers the important contextual nuances: deterministic behavior, entity-type mapping, exact vs. ranked matching, and how to interpret the output. Nothing essential is missing for an agent to invoke this tool appropriately.

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

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

The input schema already defines both parameters with descriptions and an enum for id_type, so the baseline is high. The description adds extra meaning by explaining the entity-level implications of each id_type and the underlying endpoint/search behavior, which is useful semantic context beyond the raw schema.

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

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

The description clearly states the tool resolves standard identifiers to MusicBrainz entities 'without a name search' and is 'the deterministic path when you already hold an ID.' It distinguishes itself from sibling tools like musicbrainz_search_entities and the get_* family by framing this as ID-based lookup, and it lists the exact id_type to entity-type mappings.

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

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

It explicitly explains when to use the tool: 'when you already hold an ID' and 'without a name search.' It also gives per-identifier entity outcomes (ISRC → recordings, ISWC → works, barcode → releases), which helps select this over search/browse tools. It does not explicitly name alternatives, but the intended use context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.