brand_repeat_purchaseCustomer loyalty per ASIN: repeat buyer share and repeat revenue by week.
| Name | Required | Description | Default |
|---|---|---|---|
| asin | No | ||
| limit | No | ||
| weeks | No | ||
| offset | No | ||
| period | No | ||
| seller_connection_id | No | Which seller connection (see account_sellers). Optional when the token has exactly one. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about the metrics and ASIN-level scope, but it does not reveal behavior around omitted parameters, defaults, or that 'week' is only one of several supported periods.
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 compact sentence with no filler. Every phrase contributes meaning: scope, metric type, and time granularity are all front-loaded.
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 six parameters, no required parameters, low schema coverage, and no output schema, the description is too thin. It does not clarify what happens when `asin` is omitted, how `weeks` relates to `period`, or how repeat purchase is operationally defined, leaving too much for the agent to guess.
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 only 17%, and the description compensates for very little. It implies that `asin` is the grouping dimension and mentions weekly granularity, but it leaves `weeks`, `limit`, `offset`, and the full `period` enum unexplained, and it could even mislead by suggesting only weekly data when MONTH and QUARTER are allowed.
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 states a clear analytical focus: customer loyalty per ASIN, specifically repeat buyer share and repeat revenue by week. This is concrete enough to distinguish it from sibling brand tools such as brand_market_basket or brand_top_search_terms, though it lacks an explicit verb like 'returns' or 'reports'.
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?
No guidance is given about when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or related brand tools, so an agent must infer usage from the title and metric names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.