Generate a manufacturing plan, BOM, DFM notes, and cost estimate from a product spec.
| Name | Required | Description | Default |
|---|---|---|---|
| request_id | No | ||
| payment_ref | No | ||
| product_spec | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / payment_refAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Payment Ref"
+}Input schema / properties / request_idAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Request Id"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states what the tool does (generates outputs) without mentioning side effects, required permissions, constraints (e.g., cost, time), or any behaviors like file creation or external calls. This is insufficient for an agent to fully understand the tool's impact.
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 sentence, concise with no wasted words. However, it does not front-load critical details, and the brevity sacrifices necessary context for parameter semantics and behavioral transparency. It could be reorganized to include key information without adding length.
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 tool has 3 parameters (1 required) and generates multiple outputs, but the description only mentions the input 'product spec' and not the optional parameters. The presence of an output schema partially compensates, but the description fails to contextualize the outputs or any prerequisites, making it incomplete for an agent to determine correct usage.
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%, so the description should explain all parameters. It only references 'product_spec' implicitly, ignoring 'request_id' and 'payment_ref'. The optional parameters lack any description, leaving an agent without guidance on their purpose or format. The description adds minimal value beyond the schema.
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 verb 'Generate' and the resources: manufacturing plan, BOM, DFM notes, and cost estimate. It distinguishes the tool from siblings which focus on CAD workspaces, health, and describe, making the purpose specific and unambiguous.
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 product spec is available to generate a manufacturing plan, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The context from sibling names helps infer uniqueness, but the description itself lacks direct usage direction.
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.
Each tool has a clearly distinct purpose, from workspace management to design generation and manufacturing planning, with no overlapping functionality.
Most tools follow a verb_noun pattern (e.g., create_cad_workspace, generate_cad_design), but 'describe' and 'health' are one-word names, and 'manufacturing_plan_from_spec' uses a different structure, leading to minor inconsistency.
With 6 tools covering workspace creation, design generation, export, and manufacturing planning, the count is well-scoped and appropriate for the server's purpose.
The tool set covers core workflows (create, generate, export, plan) and status checks, but lacks update/delete operations for CAD designs, which may limit iterative editing.