Structured /grep filter on registry or subset of prior search hits.
| Name | Required | Description | Default |
|---|---|---|---|
| dietary | No | ||
| price_range | No | ||
| neighborhood | No | ||
| open_tonight | No | ||
| publisher_id | No | ||
| restaurant_ids | No | ||
| accepts_reservations | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond what annotations already provide (readOnlyHint, idempotentHint). The mention of 'subset of prior search hits' adds some state dependency but lacks detail.
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 extremely short but under-specified; it sacrifices clarity for brevity and does not earn its place by being informative.
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 7 parameters, no parameter descriptions, and no usage examples, the description is grossly incomplete. It fails to explain filter logic, parameter interactions, or output context.
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 description coverage is 0%, and the description does not explain any parameter meaning or valid values. The agent must rely solely on parameter names, which is insufficient.
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 states it's a filter tool on a registry or prior search hits, making the purpose clear. However, it does not differentiate from sibling tools like search_restaurants.
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?
No explicit when-to-use or when-not-to-use guidance is provided. The description only hints at possible use cases (registry or prior hits) without alternatives.
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.
There is notable overlap among search, search_web, search_restaurants, and search_salons, as well as between filter_restaurants/filter_salons and search with constraints. However, descriptions clarify the intended vertical or corpus, and entity getters are distinct. The overlap is manageable but could cause misselection.
Names mostly follow a get_/list_/search_/register_/delete_/submit_/vote_ pattern in snake_case. Minor deviations like 'recall', 'remember', 'research', and 'travel_health' are less predictable but still readable. Overall consistent and clear.
38 tools is on the heavy side for a single MCP server, exceeding the typical well-scoped range. While the server covers multiple subdomains (search, travel disruptions, memory, feedback, research), the sheer number may overwhelm agents and suggests potential consolidation.
The tool surface covers core workflows: search and entity retrieval for restaurants/salons, disruption monitoring with standing queries and webhooks (register/list/delete), research submission/polling, and memory/feedback mechanisms. Minor gaps exist (e.g., no cancel for research jobs, no explicit entity list endpoint), but these are workable and do not break typical agent tasks.