Return the scoring thresholds ChurnLens applies to NRR, revenue concentration and the composite health score. These are bands, not measured benchmark data — the sourced benchmark figures are cited at https://churnlens.site/benchmarks.
| Name | Required | Description | Default |
|---|---|---|---|
| metric | No | Which band set to return: 'nrr', 'concentration', 'health', or omit for all. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns bands not measured data, but does not mention any other behavioral traits like idempotency or data freshness.
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 with no wasted words. The first sentence states the purpose, the second clarifies an important distinction. Efficient and well-structured.
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 (one optional parameter, no output schema), the description is nearly sufficient. It could mention the expected output format, but overall it provides adequate 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?
Schema description coverage is 100%, so the parameter is already well-documented. The description adds no additional parameter-level meaning, but the baseline of 3 is appropriate.
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 scoring thresholds for NRR, revenue concentration, and composite health score, distinguishing it from benchmark data and sibling tools.
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?
It clarifies that the output is bands, not measured benchmark data, and provides a URL for benchmarks. However, it does not explicitly state when to use this tool versus alternatives like score_saas_health.
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 distinct concept (revenue concentration, churn rate, LTV, zombie MRR, scoring bands, composite health). No two tools overlap in purpose.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., analyze_revenue_concentration, calculate_churn_rate). No mixed conventions.
6 tools is well-scoped for a specialized churn analytics server. Each tool earns its place, covering key metrics without bloat.
The tool surface covers the core churn analytics workflow: concentration, churn rates, LTV, zombie detection, scoring bands, and composite health. No obvious dead ends.
