list_ai_pack_growthList growth checkpoints, the active checkpoint, hosted slot/byte usage and limits without exposing private memory contents.
| Name | Required | Description | Default |
|---|---|---|---|
| productId | Yes | Tetrees AI Pack product id |
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 mark it as read-only. The description adds the behavioral guarantee of 'without exposing private memory contents', providing context beyond the annotations about what the tool will and will not do.
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, focused sentence that conveys the tool's purpose, content, and privacy boundary without unnecessary elaboration or repetition.
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 read-only listing tool without an output schema, the description sufficiently indicates what is returned (checkpoints, active checkpoint, usage/limits) and what is excluded (private memory). It lacks details like pagination but remains adequate for selection and invocation.
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 single parameter productId is fully described in the schema with a clear definition. The description adds no further parameter details, but schema coverage is 100%, so the baseline score 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 it lists growth checkpoints, active checkpoint, and usage/limits. It distinguishes itself by explicitly noting it does not expose private memory contents, which differentiates it from get_ai_pack_private_report among the siblings.
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 implies usage when a non-private summary of growth is needed, contrasting with get_ai_pack_private_report, but does not explicitly state when to use this tool versus alternatives or provide conditions for selection.
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.
Most tools are clearly distinct by action and resource, though several clusters (accept/propose/select/list growth, prepare/execute/run) require careful reading of descriptions to avoid confusion.
All tool names follow a consistent verb_noun snake_case pattern, with clear action prefixes and descriptive resource nouns.
With 26 tools, the set exceeds the recommended range and feels heavy, even though the domain covers publishing, runtime, growth, and reporting workflows.
The toolkit covers the main AI pack lifecycle—authoring, publishing, acquisition, running, searching, and reporting—but lacks explicit delete/revoke operations for drafts or entitlements.