List versioned validation reports for a project without implying licensed engineering approval.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds valuable context beyond them: it mentions the reports are versioned and emphasizes that listing them does not imply engineering approval. This gives the agent a clearer behavioral picture of what the tool does and does 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, front-loaded sentence that directly states the purpose and the key caveat. Every word earns its place; there is no fluff or redundancy.
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 simple list tool with one parameter, strong annotations, and an output schema, the description covers the essential context: what is listed (versioned validation reports) and what it does NOT imply (engineering approval). It is complete enough without needing to explain return formats or pagination.
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 has 0% description coverage, so the description must compensate, but it only says 'for a project' without explaining the project_id format or any additional semantics. The pattern in the schema is the only real guidance, so the description adds minimal parameter 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 action (list), resource (versioned validation reports), and scope (for a project). It also adds a distinguishing caveat about not implying licensed engineering approval, which separates it from validation/approval-related tools like validate_project.
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 clear context that this tool provides validation reports without conferring approval, implicitly telling the agent it is for informational viewing, not for sign-off. This is a useful exclusion, though it does not name alternative tools explicitly.
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.
Every tool targets a distinct resource, role, or action. For example, list_orders versus list_supplier_orders clearly separates buyer and supplier views, and update_supplier_order versus update_supplier_order_issue versus update_supplier_order_return handle different concerns despite similar names. Rich descriptions eliminate ambiguity.
All tool names consistently use snake_case with a verb_noun pattern (e.g., create_project, list_orders, update_supplier_capabilities, search_products). The style is uniform across reads, writes, lists, and searches, making the API predictable.
With 55 tools, the server far exceeds the typical well-scoped range of 3-15. Even for a broad supply chain platform, 50+ tools hits the rubric's 'extreme mismatch' threshold. The domain is comprehensive, but the sheer number overwhelms and likely complicates agent tool selection.
The tool surface covers the full lifecycle from project creation, BOM management, sourcing, quoting, planning, checkout handoff, orders, returns, issues, warranties, catalog updates, supplier profiles, and validation. It handles buyer and supplier sides with appropriate state transitions, and includes meta tools for connection and schema guidance. No obvious critical gaps exist.