Computes retention cohorts by signup month, showing the percentage of customers still active after 1, 3, 6, and 12 months.
Coortes por mês de entrada: % de clientes ainda ativos após 1, 3, 6 e 12 meses.
| Name | Required | Description | Default |
|---|---|---|---|
| as_of | No | ||
| months | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden, and it does disclose the output concept (survival percentages at fixed horizons), which is more than a bare label. However, it says nothing about whether this is a read-only computed aggregate, whether as_of defaults to today, or how cohorts with insufficient history are handled.
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 front-loaded sentence with a colon introducing the metric — no filler. It is efficient, though the extreme brevity leaves no room for the usage or parameter context the rest of the definition lacks.
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 output schema covers return values, but with no annotations and zero parameter coverage the definition is incomplete for a two-parameter analytical tool: horizon semantics, snapshot behaviour, and cohort bucketing rules are all missing. The Portuguese-only text among English sibling descriptions also reduces discoverability.
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 0% and the description never mentions either parameter. The meaning of 'as_of' (format, default of null, whether it snapshots the analysis) and 'months' (default 12) is left entirely undocumented; worse, the stated fixed windows of 1/3/6/12 months could be misread as overriding the months parameter.
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 names a specific analytical resource (retention cohorts keyed by entry month) and the exact metric computed (percentage of customers still active at 1, 3, 6 and 12 months). That is enough to separate it from siblings like churn_by_month or churn_reasons, though it never explicitly contrasts itself with them.
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?
There is no statement of when to use this cohort view versus churn_by_month, churn_by_segment, or run_sql, and no conditions, prerequisites, or exclusions are given. The agent must infer usage purely from the metric described.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.