Get the AI-optimized property manifest in schema.org format with lilo extensions. Available in YAML, JSON, or JSON-LD format. Use this for structured data integration and AI agent consumption.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format: yaml, json, or jsonld (default jsonld) | |
| property_id | Yes | Property UUID or lilo_code |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. It adds context about available formats and schema.org/lilo extensions, but doesn't disclose other behavioral traits such as whether the manifest includes pricing or availability, pagination behavior, or error handling. With annotations covering the safety profile, this is adequate but not extra informative.
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 three sentences: purpose, formats, and usage context. Each sentence is purposeful and free of fluff. It's front-loaded and appropriately sized for a simple tool.
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?
The tool is simple with two well-described parameters and read-only annotations. The description conveys what the manifest is (schema.org + lilo extensions), the formats, and the intended use case. It could mention what content the manifest contains, but for a simple read-only retrieval tool, it's 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%, as both format and property_id are described in the input schema. The description's mention of YAML/JSON/JSON-LD repeats the schema's format enum without adding new meaning. Baseline 3 is appropriate since the schema does the heavy lifting.
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 retrieves an 'AI-optimized property manifest' in schema.org format with lilo extensions, specifying the verb (Get), resource, and format. It is distinguishable from siblings like get_vacation_rental_identity_manifest by the 'AI-optimized' focus, though it doesn't explicitly name alternatives.
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?
Explicitly states 'Use this for structured data integration and AI agent consumption,' providing a clear context for when to use the tool. It lacks explicit exclusions or mention of alternative tools, but the use case is specific enough.
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.
