suggestGet autocomplete candidates for skills, occupations, places, or employers from the start of a word or phrase, matching Platsbanken search behavior.
Free-text suggestions (skills, occupations, places, employers) from the start of a word — as in Platsbanken.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Start of a word or phrase, e.g. "utv" | |
| limit | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description still adds real behavioral value by specifying prefix-matching semantics ('from the start of a word') and the domains matched, though it says nothing about result ordering, caps, or locale of the underlying data.
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 dense sentence, front-loaded with the core action and followed by the entity domains; every clause carries information and nothing is repeated from the schema.
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 two-parameter read-only tool with annotations covering safety, most of what an agent needs is present. However, there is no output schema and the description never states what a suggestion response looks like or how many items come back, leaving 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?
Schema coverage is 50%: q is documented with an example and limit is self-explanatory via its constraints. The description adds meaning by indicating q matches the start of words across several entity types, but gives no further detail on how results are limited or ranked, so it only marginally compensates for the undocumented limit parameter.
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+resource: free-text autocomplete suggestions, and enumerates the concept domains (skills, occupations, places, employers). It does not explicitly distinguish itself from the similar-sounding sibling search_taxonomy, so an agent must infer the boundary between autocomplete and taxonomy search.
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?
"From the start of a word" implies prefix-style lookup and thus hints at usage, but there is no explicit when-to-use, when-not-to-use, or pointer to an alternative such as search_taxonomy for full-term search. Context is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.