model_names_and_idsRetrieves a mapping of every Anki note type name to its model ID, helping AI assistants resolve note types for flashcard operations.
Returns an object mapping every model (note type) name to its model ID.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v3.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuine value by disclosing the return shape (a name→ID object) and the completeness guarantee ('every model'), which matters because no output schema exists. It says nothing about ordering or how large the set may be.
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?
A single sentence that leads with the return type and delivers the key distinction (IDs, not just names) with zero filler. No redundancy against the title, which only says 'List note types with IDs'.
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?
For a zero-param, read-only listing tool with no output schema, the description supplies the essential missing piece: the return structure. What is absent is routing guidance relative to the very similar sibling model_names, which leaves a small but real gap.
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 tool takes zero parameters, so the baseline is 4 and there is no input semantics for the description to compensate for. Nothing in the description misrepresents the (empty) input contract.
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?
States a specific verb ('Returns') and resource ('an object mapping every model (note type) name to its model ID'), and the parenthetical resolves the model/note-type terminology an agent may not know. It implicitly separates itself from sibling model_names by including the ID, though it never names that sibling explicitly.
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?
Usage is only implied: an agent can infer it should call this when it needs the numeric model ID rather than just names. There is no explicit when-to-use statement, no exclusion, and no pointer to model_names for the names-only case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.