Search Philadelphia historic properties and landmarks from public records. Useful for World Cup 2026 and America's 250th Anniversary (2026) planning. Filter by type: landmark, historic_religious, african_american, or all.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Property type filter | |
| limit | No | Max results (default 20) | |
| query | No | Search query (property name, address, etc.) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's a safe read operation. The description adds that the data comes from public records and mentions the type filter, but does not disclose return format, pagination, or any other behavioral details. This adds some value beyond annotations but not a lot.
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?
Two sentences, front-loaded with the main purpose. The second sentence adds filter options and context without redundancy. Every word earns its place; no fluff or repetition.
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 simple search tool with three optional parameters, read-only annotations, and no output schema, the description covers the core functionality, filter options, and relevant use cases. It doesn't explain the return value shape, but that is less critical for a search tool with a self-explanatory name. Overall, it is sufficiently complete.
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 100%, so all three parameters (type, limit, query) have descriptions. The description repeats the type enum and adds context for the use case, but does not meaningfully enhance the semantics of limit or query. Baseline 3 is appropriate when schema already documents parameters.
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 Philadelphia historic properties and landmarks from public records, using a specific verb and resource. It distinguishes from sibling tools like get_philadelphia_landmark_details (details vs search) and search_philadelphia_event_venues (different resource).
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?
Provides explicit context for use in World Cup 2026 and America's 250th Anniversary planning, which helps an agent decide when to invoke it. It also lists the type filter options. However, it does not name alternative tools or state when not to use it, so it's clear context without exclusions.
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 significant overlap and redundancy among tools, causing ambiguity. For example, analyze_booking_threat_risk, analyze_guest_communication_risk, and analyze_guest_interaction_risk are aliases or near-duplicates, and multiple tools like get_vacation_rental_details and fetch_vacation_rental_details appear to serve the same purpose. This makes it difficult for an agent to choose the correct tool without confusion.
Most tools follow a consistent verb_noun pattern (e.g., check_vacation_rental_availability_and_pricing, get_vacation_rental_details), which aids readability. However, there are minor deviations, such as some tools using 'analyze' vs. 'assess' or 'detect' for similar risk functions, and a few tools like 'ingest_philadelphia_public_records' use a different verb style, but overall the naming is largely predictable.
With 67 tools, the count is excessive for a vacation rental server, leading to bloat and potential overwhelm. Many tools could be consolidated (e.g., multiple risk analysis tools, duplicate property detail fetchers), and the scope feels unfocused, including niche tools like those for Philadelphia events or World Cup compliance that might be better handled as parameters in broader tools.
The tool set provides comprehensive coverage for the vacation rental domain, including booking, risk assessment, compliance, maintenance, evidence management, and guest interactions. There are no obvious gaps; it supports full CRUD/lifecycle operations and specialized workflows, ensuring agents can handle most scenarios without dead ends.
