Run the current versioned validators and return separate blocking errors, compatibility conflicts, warnings, missing information, passed checks, and unavailable checks.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| validation | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations do not provide meaningful hints (all false), so the description carries the burden. It does disclose the behavioral output format (separate categories of results), which goes beyond the annotations. However, it does not mention whether running validators has side effects, such as creating a validation run record, which is relevant given readOnlyHint is false.
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, well-structured sentence that front-loads the action and clearly lists expected result categories. Every word contributes to understanding what the tool does, with no redundancy or 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?
Given the simple schema and presence of an output schema, the description covers the core action and result categories adequately. However, it lacks guidance on usage context, potential side effects, or differentiation from list_project_validations, leaving moderate gaps in overall completeness.
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 input schema has a single required parameter 'project_id' with a pattern but no description. The tool description does not mention project_id at all, nor does it explain how the parameter is used, resulting in 0% schema description coverage. The parameter name and pattern are self-explanatory to some extent, but the description adds no additional semantic meaning.
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 uses a specific verb ('Run') and resource ('current versioned validators'), and clearly enumerates the distinct output categories (blocking errors, compatibility conflicts, etc.). This distinguishes it from the sibling tool list_project_validations, which merely lists validations rather than running them.
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 for running validations and obtaining categorized results, but it does not explicitly state when to prefer this over list_project_validations or mention any prerequisites. No alternatives or exclusion criteria are provided, so guidance is only implicit.
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.