Get metadata about when this dataset was last calculated and what period of sale/rental data it covers. Call this before presenting any number as 'current' - the underlying data is refreshed monthly, not in real time.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description discloses critical behaviors: data is 'refreshed monthly, not in real time' and returns metadata. It implies read-only nature. Sufficient for a metadata tool.
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, no wasted words. First sentence defines purpose, second provides actionable guidance. Ideal conciseness.
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 zero parameters and an output schema (present but not shown), the description covers what the tool returns and why to use it. Complete for the tool's simplicity.
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?
No parameters exist, so baseline is 4. Description adds no param info but none is needed.
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 it 'gets metadata about when this dataset was last calculated and what period...it covers', with a specific verb and resource. It distinguishes from siblings like get_sample_data which retrieve actual data.
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 advises to 'Call this before presenting any number as current', providing context for when to use. Does not mention alternatives, but siblings are different dataset types so no confusion.
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.
Each tool has a clearly distinct purpose: data freshness, sample data, and listings for condos, HDB towns, and landed projects. No overlap.
All tool names follow a consistent verb_noun pattern (get_*, list_*) using snake_case, making them easy to understand.
Five tools is slightly on the smaller side but appropriate for a data portal's free tier; each tool serves a specific discovery or metadata function.
The tools cover discovery and metadata but lack any actual data retrieval endpoints (e.g., stats for districts or projects), which are described as paid. This leaves agents unable to complete core property data requests.