upload_ai_packRead an explicit local .taip path, transfer it through the product-scoped private upload contract, and commit one immutable higher version.
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | ||
| packPath | Yes | ||
| changelog | No | ||
| 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?
The description discloses that the action commits an immutable higher version, indicating a write operation with lasting side effects. However, it does not mention failure modes, version conflict behavior, access requirements, or whether the operation is atomic or reversible.
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 concise sentence with no redundant wording. It efficiently conveys the action, target resource, and versioning outcome.
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?
With four parameters and only 25% schema coverage, the description does not fill enough gaps. It omits parameter-specific behavior, return values, and potential side effects such as version immutability constraints, making the tool under-specified for reliable autonomous 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?
Only productId has any description, and it is minimal. The required packPath and version parameters lack direct descriptions, and changelog is unexplained; the .taip path is indirectly referenced in the operation description, but semantics for version and changelog remain unclear.
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 uploads and commits a .taip pack as an immutable higher version, which distinguishes it from related operations like upload_ai_pack_image or update_ai_pack_draft. Some jargon like 'product-scoped private upload contract' adds mild ambiguity, but the core purpose is concrete.
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 gives no explicit guidance on when to choose this tool over alternatives such as upload_ai_pack_image, create_ai_pack_draft, or publish_ai_pack. It implies a private product-scoped upload, but does not state usage conditions or exclusions.
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.