View all tracked data sources with AI-readability assessment. Shows which rental sites AI can read, which are partially readable, and which block AI entirely.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It explains the output (readability categories) but omits side effects (none expected), authentication needs, rate limits, or data freshness. The read-only nature is implied but not explicitly stated.
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 sentence that is front-loaded and conveys all necessary information. No redundant words; every part 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?
Given the tool's simplicity (no parameters, no output schema, straightforward read operation), the description is sufficiently complete. It covers the tool's purpose, output, and scope without requiring additional 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?
The tool has zero parameters and 100% schema description coverage, so the description need not add parameter meaning. The baseline score for 0 parameters is 4; the description adds no extra parameter info but that is acceptable.
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's purpose: 'View all tracked data sources with AI-readability assessment.' It specifies the resource (tracked data sources) and the assessment categories (readable, partially readable, blocked). This distinguishes it from sibling tools like rental_search or rental_stats.
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 implies use when checking AI-readability of rental sites, but provides no explicit guidance on when to use or avoid this tool versus alternatives. No usage examples or exclusions are given, leaving the agent to infer context.
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.
Most tools target distinct actions, but the presence of both 'search' and 'rental_search' could cause confusion, and 'fetch' overlaps slightly with 'rental_property'. However, descriptions clarify the differences.
While most tools use a 'rental_' prefix, two tools ('fetch', 'search') lack it, and the naming style varies between verb-noun and noun-only (e.g., 'rental_availability' vs 'rental_search'). This inconsistency could confuse an agent.
With 16 tools, the set covers a comprehensive range for a Caribbean rental assistant, including search, property details, pricing, availability, licensing, market intelligence, and session management. Each tool serves a clear purpose.
The tool set covers the core lifecycle (search, view details, create sessions, add picks), but lacks session update/delete functionality. Also, 'fetch' and 'search' seem redundant with rental-focused tools. Overall, the domain is well-covered for an agent workflow.