get_growth_metricsReturn enabled, partial, contract-only, and unavailable growth metrics with privacy and interpretation boundaries.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| schema | Yes | ||
| metrics | Yes | ||
| privacy | Yes | ||
| interpretation | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful context about metric categories and privacy/interpretation boundaries, but it remains vague about what those boundaries entail and does not detail any behavioral quirks beyond the annotations.
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 a single front-loaded sentence that immediately states the action and resource, then lists the returned categories and boundaries. There is no filler or redundancy, and every phrase adds meaning.
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 zero-parameter, read-only tool with an output schema and strong annotations, the description covers the core behavior and return categories adequately. It is arguably complete enough for invocation, though terms like 'contract-only' and 'interpretation boundaries' are not expanded, and no usage context is given.
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 baseline is 4. The description does not need to explain parameters, and it does not introduce any parameter-related ambiguity.
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 returns growth metrics categorized as enabled, partial, contract-only, and unavailable, and mentions privacy and interpretation boundaries. It is specific and generally clear, but it does not explicitly differentiate from sibling tools such as get_niulai_info, so it stops short of the highest score.
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 provides no guidance on when to use this tool versus alternatives like compile_query_plan, get_niulai_info, or search_agents. There are no exclusions, prerequisites, or decision rules, leaving the agent to infer usage from the tool name alone.
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 targets a clearly distinct area: query compilation, growth metrics, entity-specific information, and agent registry search. There is no meaningful overlap or ambiguity between them.
All tool names follow the same snake_case verb_noun pattern: compile_query_plan, get_growth_metrics, get_niulai_info, search_agents. The naming is predictable and internally consistent.
Four tools is a focused, manageable set for a read-only public-data information server. Each tool has a distinct role and none feel redundant or missing from the core scope.
The set covers the main read-only capabilities: query plan compilation, metrics retrieval, publisher/entity details, and agent discovery. Minor gaps exist, such as no query execution or full agent detail endpoint, but these appear intentionally outside the stated scope.