get_ai_pack_private_reportRead actionable owner-only failures and next actions without exposing them to buyers.
| 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 declare readOnlyHint=true, so the description does not need to restate that. The description adds valuable context about the private nature of the data (owner-only) and privacy implications (not exposing to buyers), exceeding the annotation baseline.
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, clear sentence with no redundant words. It efficiently conveys the purpose and key distinction without unnecessary detail.
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?
There is no output schema, so return values are not required. The description provides enough context for an agent to understand the tool's purpose, input, and privacy model, making it complete for its scope.
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 schema describes productId as 'Tetrees AI Pack product id' with 100% coverage. The description adds no extra detail about the parameter beyond what the schema already provides, so it meets the baseline for high schema coverage.
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's function: reading owner-only failures and next actions. It also distinguishes it from a public report by mentioning 'without exposing them to buyers,' which contrasts with the sibling 'get_ai_pack_report'.
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 when to use this tool: when you need owner-only feedback and want to avoid exposing it to buyers. It indirectly references the alternative (public report) and provides a clear condition, though it could be more explicit about ownership requirements or when to prefer the public report.
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.