searchSearch Dim Hour's restaurant, bar and venue catalog across all 24 cities. Returns ranked venues with a dimhour.com link for each. Use for questions about where to eat or drink — by cuisine, dish, neighborhood, city, vibe, or award.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What to look for, e.g. 'best ramen in NYC', 'michelin dallas', 'rooftop bar miami' |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false. The description adds useful behavioral context by specifying that results are ranked venues and include a dimhour.com link for each. There is no contradiction with annotations.
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 two sentences with no filler. The tool's purpose and scope are front-loaded, followed immediately by query guidance. Every sentence earns its place.
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 tool with one required parameter, an output schema, and annotations covering safety and scope, the description is complete. It explains what the tool searches, what results look like, and what kinds of queries to use it for. No critical information is missing.
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 schema already documents the single query parameter with examples, so baseline is 3. The description adds meaningful semantic guidance by enumerating what kinds of queries are supported (cuisine, dish, neighborhood, city, vibe, or award), going beyond the schema's examples.
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 searches Dim Hour's restaurant, bar, and venue catalog across 24 cities, and that it returns ranked venues with dimhour.com links. It does not explicitly differentiate from the sibling 'search_venues', but the scope and output are specific enough for an agent to understand the core function.
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?
The description gives clear guidance on when to use this tool: 'questions about where to eat or drink' and lists query facets like cuisine, dish, neighborhood, city, vibe, or award. It does not mention when not to use it or point to alternatives such as list_curated or search_venues, but the use context is otherwise well defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
fetch and get_venue both retrieve essentially the same full venue record, differing only by an extra long-form story field. Similarly, search and search_venues both search the same catalog and return ranked venue results, making it unclear which one an agent should call and creating real misselection risk.
The list_* tools are consistent and readable, and most tools use snake_case verb_noun naming. However, fetch and search are bare verbs, and fetch vs get_venue introduces two different verbs for the same operation, so the overall pattern is mixed but still understandable.
Seven tools is a reasonable size for a venue guide server, but the count is slightly padded because fetch duplicates get_venue and search duplicates search_venues. The effective surface is closer to five distinct tools, so the count is slightly over what is needed.
The read-only domain is well covered: city discovery, search, curated editorial lists, new venue updates, and full venue details are all present, and search naturally leads into detail retrieval. Minor gaps exist, such as no dedicated non-search way to browse all venues in a city, but the core workflows have no dead ends.